Faculti des h d e s sup&ieurcs

Gait asymmetry in able-bodied subjects using biomechanic dab

Heydar Sadeghi

a it6 &dub par un jury compose des penonnes suivantes:

Dr. Jean Marc LAVOIE President du jury

Dr. Paul ALLARD D i e u r de recherche

Dr. Hubert LABELLE Member du jury

Professor. Jean-Pierre BLANCHI Examinateur externe

Dr. Denis GRAVEL Representant du doyen

Thbe accept& le: January 1999

Humbly dedicated to my father

Mohammad Bagher Sadeghi

RESUME

Marcher est une activiti humaine univedle qui prtsente un grand int* dam

d i f f h t s domaines applicables aux sports, I'valuation cl ique, les

diagnostiques, la rihabilitation, la conception de membres artificiels et la

robotique. La comp~hension des differents aspects de la marche se fait 3vec

une sophistication croissante des moyens techniques et de la participation de

plusieurs champs scientifiques.

Traditionnellement et pour simplifier I'analyse de la marche, on suppose

que les membres infirieurs ont des actions symitriques. L'objet g b 5 a l de cene

itude itah de v&fier cene hypothkse par I'identification et la classification des

puissances musculaires en trois dimensions, des hergies mkaniques asocikes

et de diterminer lesquels de ces paramttres sont reliis aux fonctions de

propulsion et d'iquilibre. De plus. ce projet de recherche avait pour but de

diterminer comment la propulsion et le contr6le de chaque membre s'effectue et

comment ces fiches sont dparties entre les membres inf&eures. Nous

avanqons aussi I'hypothk que I'activitt b e jambe est dipendante de I'rutre

lors de la marche.

Des donnkes bilathles, tridimensionnelles et simultankes de dix-neuf

jeunes hommes droitiers des pi& et des mains furent recueillies au moyen de

huit camhas vidb synchronides i deux plates-fonnes de force. La puissance

musculaire et l'hergie mkanique des membres infhieun h t calculks i

chaque articulation et dam chaque plan au moyen de la technique de calcul de

dynamique inverse La methode de l'analyse en composautes principales (ACP)

a &ti appliquie pour riduire et classer 54 p a r a m h de la marche pour chaque

jambe. Un test t de Student a &C appliqui aux donnks appar ik pour

diterminer une diffnce datimque entre ces p a r a m h de la marche. La

rnkthode de cordation de Pearson f i t utilisie pour daerrniner I'mtcraction des

param* au niveau de chaque membre inferieur. Enfin, une analyse de

corrilation canonique a CtC utiliske pour estima l'interaction entre les membres

infkieurs au cours de la marche.

Le membre inferieur qui a m e fonction de propulsion a Ctt caractkie

par une plus forte phase de po&. La plupart des p a r a m b identifik par

I'analyse ACP Ctaient associb i la hanche a se situaient principalement dans le

plan sagittal. Ces pyamitres concemaient la phase de poussk. La pCriode de

propulsion debute au moment oh le talon touche le sol et se maintient pendant

la phase de support. Une deuxikne fonction de support apparaissait au cows de

la moitie de la phase de support. La tiche p ~ c i p a l e de la jambe gauche ttait le

contr6le comrne nous l'avons monfn5 &ice i la bouffk de puissance i la

hanche et au genou La ghkation de puissance par la jambe controlathle

ttaie secondaire. Son r6le principal ttait d o n le contr6le de I'activitt et

I'ajustement de la propulsion de l'autre jambe. Ces h l t a t s contredisant

lhypothise que la cheville a une contribution majeure dam la marche. De plus,

l'itude met en &dace une relation fonctionnelle entre les membres infkieurs,

une fonction de propulsion t droite a une fonction de mntr6le t gauche, cme

dernih K situe dam les plans hntal a transverse.

ABSTRACT

Walking as one of the most universals of all human activities is of in~m and is

applicable to sports, clinical evaluations, d i e 5 rehabilitation, and artificial

limb designs as well as to robotics Understanding diffacnt aspects of gait

function has been increasing with aMilability of sophisticated and advanced

klnunents and involvement of other areas of sciences as well as applying

advanced satistical methods.

Traditionally, symmetry between lower limb has been assumed for

simplicity in gait analysis. The g e n d purpose of this shady was to examine

symmetry assumption by mean of identifying the beedimensional muscle

powers and aSSOciated mechanical energies and to detamine which of these gait

parameters were related to propulsion and support. Furthermore, this research's

project has focused on to test how propulsion and control tasks performed by each

limb and how these tyks are managed between the lower limbs. In this regard we

postulated that limb propulsion is mainly associated with the interaction of a

number of muscle power bursts developed throughout the stance phase while

control actions are mainly achieved by the contralateral limb through a different

power burst interactions. Moreover, we hypothesize that the power activities of a

limb are related to those of the contra-latd limb.

Simultaneous bilateral three-dimensional data of nineteen young, healthy,

right handed and leg dominant male subjects was assessed using an eight camera

video-based system synchronized to two force plates. The muscle powers and

their related mechanical energy were calculated at each joint and in each plane of

the lower limbs by means of the inverse dynamic technique. The principal

component analysis (PCA) method was applied to reduce and clasify 54 gait

parametetx for each limb. Student's t-test for paired data was applied to determine

significant differences W e e n the identified gait p a m e t a s and the Pearson

correlation method was used to determine the interaction among each limb data

sets. Furchamore, Canonical correlation malysis was used to determine the

interactions between the right and left lower exmdty gait data sets.

The l i b that had a propulsion function was characterized by a strong third

hip power at push o& Most of the parameten identified by the PCA were

assoCiated with the hip, and were mainly in the sagittal plane. These parameters

were concentrated during push+& Gait propulsion was an activity initiated by the

hip shortly after heel-strike and maintained throughout the stance phase. T h m

was a secondary support function that occurred during midstance. Control was the

main task of the left l i b as evidenced by the power absorption bursts at the hip

and knee. The contralateral l i b power generations were generally secondary to

control activities and were possibly involved in c o d o n adjustments of the other

lib's propulsion T h e d t s do not support the hypothesis that the ankle was a

major contributor to f o d progression Inter-limb interaction further

e m p W the functional relationship between forward progression n d control

tasks developed by each l i b and highlighted the importance of the hn ta l and

transverse plane actions during gak

ACKNOWLEDGMENT

I am fortunate to have had the help of some truly great people in the

completion of this w o k These include professicinal colleagues who have

provided scientific input but also friends and family whose support has been

equally important

I would like to give a special *- to my thesis supenisor, Dr Paul

Allard who is professor at the Kinesiology Department and adjunct professor at

Mechanical Enginwring Department of Ecole Polylenlique de Montreal and

director of the Movement Labomtory at the Research Center of Sainte Justine

Hospital for his d i d o n , advice and undemanding.

I am also indebted to Dr. Moms Duhaime. Orthopeadic surgeon and

professor in Orthopeadic surgery at Shriner's Hospital as my co-advisor who

has become a valued friend and a mentor to me throughout my PH.D project

I would also like to expms my sincere thanks to Dr. Hubert Labell.

Oahopeadic surgeon at Sainte Justine Hospital, and Professor Jean Blanchi, the

head of the Physical Activity Science Department of the Joseph Fourier

University in France, and Dr. Gravel h m Rehabilitation Department of the

Montreal University for accepting to be in my PhD. defense committee.

I would like to see a part of this degree is conferred on my wife,

Maryam. I tend to t h i it is appropriate. Something tangible should mark her

contribution to this thesis. A thanks just doesn't cut i t

I deeply appreciate to the Ministry of Culture and Higher Education and

Tarbiat Moallem University of the Islamic Republic of Iran for financial

assistance.

LET OF FIGURES

CILIPTER2 BASIC AND ESSENTIAL KNOWLEDGE FOR GAIT ANALYSIS

Fig 2.1. The anatomical positions, with respect to the three reference planes and ............................................................. six fundamental i d o m 9

..................... Fig 2.2. Movements about the major joints of the lower limb.. 10 Fig 2.3. Bones and joints of the lower limbs ........................................... 11

.............. Fig 23. Coordinate system for lower limb showing the global axes ..I3 Fig 25. Superficial muscles of the right leg.. .......................................... 14 Fig 2.6. F i determinant of gait pelvis rotation reduce the angle of the hip

flexion and extension. which in turn reduce the vertical movement of the hip.. .................................................................................. - 2 5

Fig 27. Second determinant of gait The vertical movement of the center of mass is less than that of the hip, due to pelvis tilt ..................................... 26

Fig 2.8. Third, fourth and filthe determinants of gait: Stance phase. knee flexion shortens the leg (third); the heel lenghtens it (fourth); so does the forefoot (filth).. ................................................................................. 28

Fig 2.9. Sixth determinant of gait having the feet closer together reduces the side- to-side movement of he center of gravity necessary to maintain balance ................................................................................ .30

Fig 2.10. Profile views of the human gait laboratory illustrating data collection system.. ................................................................................ 34

............................... Fig 2.1 I. The spechum of a signal with additive noise 39 ................ Fig 2.12. Response of low-pass filter introduced to reduce the noise 40

............................ Fig 2.13. Spectrum of the output waveform after filtering 41 Fig 2.14. The three angular degrees of M o m (or Euler angles) defining the

orientation of a segment's refrence axes relative to the global reference system

CHAPTER 4 PAPERS

PAPER 1. Fig. 1 Joint a) moments and b) muscle powers developed at the ankle in ten able-

bodied men.. ......................................................................... 3 0 Fig. 2 Joint a) moments and b) muscle powers developed at the knee in ten able-

bodied men ............................................................................. 81 Fig. 3 Joint a) moments and b) muscle powers developed at the hip in ten able-

bodied men ........................................................................... 81 Fig. 4 Joint a) moments and b) muscle powers developed at the ankle in fifteen

able-bodied women. ................................................................... 90 Fig. 5 Joint a) moments and b) muscle powers developed at the knee in fifteen

able-bodied women. ................................................................. .90

Fig 6 Joint a) moments and b) muscle powers developed at the hip in fifteen able-bodied women... ...................................... .-. .................... -91

PAPER 2. Fig. 1. Powers developed at the right a) hip, b) lsee and c) ankle, during natural

speed walking in 19 able-bodied subjects. The vertical lines indicate the begining and the end of the double support period ........................ -1 12-1 15

Fig. 2. Powm developed at the left a) hip, b) knee and c) ankle, dllring natural speed walking in 19 able-bodied subjects. The left limb gait cycle is overlaid on right limb gait cycle, and begins at the 11% mark ............................................................................. 114-1 15

Fig. 3. Factor loading of the peak powm and mechanical energies of the right limb ..................................................................................... 118

Fig. 4. Factor loading of the peak powm and mechanical enagies of the left . .

limb.. .................................................................................. 1 19

PAPER 3. Figure 1: Three dimensional a) hip, b) knee and c) ankle muscle power c w e s

developed at the right (solid line) and lea (dash lme) lower limb by the 19 able-bodied subjects gait The dashed line rep=& one standard deviation h r n the mean. ....................................................................... 143

Fig 2: The fust canonical correlation for the right and left limb interact having a weffiicient canonical root of 0.83 wO.001) ............................ ..A

LIST OF TABLES

CHAPTER2 BASIC AND ESSENTIAL KNOWLEDGE FOR GAIT ANALYSIS

Table 2.1. Phases and paiods in the gait cycle ........................................ 16 Table 2.2. Global gait parameter with their standard deviations (SD) for able-

7.7 .............................................................. bodied, male subjects- - Table 23. Power generation, absorption and transfa functions in the lower

exmmities. ........................................................................................... 52

CHAPTER 4 PAPERS

PAPER 1. Table 1 Anthropometric data for the male and female able- bodied groups.. ... .75 Table 2 Phasic parameters for an able-bodied men group and two subjects of

that group ............................................................................... 76 Table 3 Energies in Jikg 10' developed by the right in the sagittal plane for

men ................................................................................... -83 Table 4 Energies in Jikg 10' developed by the right S i b in the hntal plane for

men .................................................................................... 83 Tabla 5 E n ~ e s in Jikg 10: developed by the right limb in the transverse plane

for men.. ............................................................................... 83 Table 6 Energies in Jkg 10' developed by the men able-bodied group in the

sagittal plane by both limbs .......................................................... 84 Table 7 Energies in Jikg 10: developed by the men able-bodied group in the

hntal plane by both limbs .......................................................... 84 Table 8 Energies in Jkg 10' developed by the men able-bodied group in the

..................................................... transverse plane by both Sibs. 85 Table 9 Phasic parameters for an able-bodied women group ...................... 90 Table 10 Energies in Jkg 10' developed by the women able-bodied group in the

sagittal plane by both Sibs .......................................................... 93 Table 11 Energies in Jikg 10' developed by the women able-bodied group in the

hntal plane by both limbs ........................................................... 93 Table 12 Energies in Jkg 10: developed by the women able-bodied group in the

transverse plane by both limbs ...................................................... 94

PAPER 2. Table 1: Temporal and phasic gait parameters of 19 able-bodied

individuals.. .......................................................................... 1 12 Table 2. Peak powers and energies common to both limbs and to the right and

............................................................................. left limbs 116

PAPER 3. Table 1 : Right limb factor loadin& peak powas, mechanical energies and

temporal parameters with their corresponding standard deviations in parenthesis ............................................................................ 145

Table2 : Left limb faaor loading, peak powas, mechanical energies and temporal parameters with their corresponding standard deviations in parenthesis.. ........................ ...

Table 3: Pearson combion coefficient values for the right and !eft lower limb peak powers (P) and mechanical energies (E) .................................. 147

Table 4: Canonical faaors of the right and left limbs using the eight gait peak power (P) and mechanical energy (E) of the right limb and the 15 of the left limb as well as the temporal gait parameters.. ............................... ..I49

ABBREVIATIONS

Three Dimensional

Advanced Mechanical Technology

Analysis of Variance

Canonical Correlation Ana!ysis

Table of contents

Resume ........................................................................................... i Abstract ......................................................................................... iv

............................................................................. Acknowledgement vi Li of figures ................................................................................. vii List of tables .................................................................................. k Abbreviations .................................................................................. x

Chapter I : Introduction

1 . Introduction ................................................................................ 1 1.1. Nature of gait data .................................................................. 2 12 . Rationale .............................................................................. 3 1 3 . Structure of the thesis ................................................................ 6

Chapter Il : Fundamentals of gait analysis

................................................................................. Human walking 7

Section 1 . Basic knowledge ................................................................. 8 1 . 1. Anatomical terms .................................................................. -8 1.2. Muscles .............................................................................. 13 13 . Gait cycle definition ............................................................... 14 1.4. Temporal parameters ............................................................... 19 1.5. Locomotor function ................................................................ 23 1.6. Gait determinants ................................................................ -24

Section 2. Gait assessment .............................................................. 30 2.1. Temporal and spatial measurement systems .................................... 31 22 . Kinematic measurement systems ................................................. 32 2.3. Kinetic measurement systems .................................................. 42 2.4. Anthxupomehy measurements .................................................. .44

........................................................................ 2.5. Gait models 45 2.6. Sources of e m r .................................................................... 48 2.?. Gait parameters .................................................................... 50 2.8. Statistical approaches and gait analysis ........................................ 53 2.9. Summary ........................................................................... 58

Chapter 111 : Literature review

............................................................................. 3.1 Introduction 60 3 2 Able-bodied gait analysis ............................................................. 60 3.3 Gait symmetrylasymmetry ............................................................ 61

3.3.1. Definitions of symmelry .................................................. 61 332 Motor control ............................................................... 62 3 3 3 . Physics of asymmetry ...................................................... 64

............................................... 33.4. Gait analysis and symmetry 65 ............................................................ 33.5. L i b dominance 67

..................................................... 3.3.6. Gait symmetry indices 69 3.4. Purpose of this study ................................................................... 70

Chapter N : Papers

Paper 1 : Men and women able-bodied gait .......................................... 72

Paper 2 : Functional gait asymmetry in able-bodied subjects .................... 103

............... Paper 3 : Muscle power relationship in bilateral able-bodied gait 130

Chapter V : General discussion

5 . Introduction ............................................................................ 165 5.1. Issues .............................................................................. 167

5.1.1. Asymmetry influence on the standardization of able-bodied gait pattern ..................................................................... 167

5.1.2. Importance of gait parameters identification on asymmetry ...... 168 5.1.3. Implication of asymmetry on gait analysis ........................... 171

5.2. Limitation ......................................................................... 172 5.3. Retrospective analysis and comments for further studies ................... 176

Chapter VI : Conclusion

................................................................................. Conclusion 180

................................................................................... Reference 183

I - INTRODUCTION

1. Introduction

Few human activities generate as much interest as locomotion. For

example, leaming to walk is the most anxiously awaited developmental milestone

by parents and grandparents. Interest in walking is not limited to infants.

Therapists and physicians often relate that the first question asked by patients with

back and leg injuries is, will I be able to walk again? Similarly, individuals with

even a long-standing paraplegia often report that they dream of walking.

Despite our fascination and years of scientific inquiry, we still do not filly

understand how we manage to get from one point to another in an upright

position Bipedal gait is essentially a human activity and it is not an easy task

The central nervous system (CNS) somehow must generate the locomotion

pattern, generate appropriate propulsive forces, modulate changes in center of

gravity, co-ordinate multi-limb trajectories, adapt to changing conditions and

changing joint positions, co-ordinate visual, auditory, vestibular and peripheral

afferent i n f o d o n , and account for the viswelastic properties of muscles It

must do al l of this within milliseconds and usually in conjunction with

coordinating a wdtitude of other bodily functions and movements.

1.1. Nature of gait data

Gait analysis is the systematic study of walking. Normal human walking

as the most common of all human movements requires the interaction of body and

its environment Walking can be defined as a method of locomotion involving

the use of the two legs, alternately, to provide both support and propulsion

(Whittle, 1991). It is one of the most difficult tasks that we learn but, once

learned, it becomes almost subconscious. Only when injury, disease,

degeneration or fatigue disturbs walking, we d m our limited understanding of

this complex biomechanical process. Over the past few years, there has bem an

increasing interest in the subject, particularly among researchers in physical

therapy, bioengineering, and several branches of medicine, including otthopedics,

rheumatology, neurology and rehabilitation

Selection interest parameters, measmments, data processing, and

interpretation are four important subsections of gait analysis. There are strong

interactions among all four subsections.

Chapter I - Imvduaion 3

Many desQiptors are needed to completely describe gait in term of the

biomechanics involved. Temporal parameters should be considered since, they

are the basic quantification descriptors of gait, and some of them play an

important role. Furthermore, the exhautive $3 analysis requires variables to

d-he the causes of movement rather 'han the movement. Moreover, though

temporal and phasic gait parameters, joint angles and muscle moments m y be

used to charJa& gait pattems, muscle powers are more convenient since they

lump both kincnatic and kinetic i n f o d o n as well as the functional role of the

muscles zs they shorten or lengthen under tension. The time integral of each

power phase, work, quantifies gait as single value parameters.

In this ngard, there is a need for measurement systems and software to

support our subjective visual impression and enable objective analysis @egg et

al. 1989). These systems have been developed during this cenhuy and becoming

more pow& and complex. However, the results in a large number of

interactive parameters, made i n t a p d o n of gait data extremely difficult.

Consequently, variable charaaerization will be important in gait analysis, when

dealing with huge databases.

1.2. Rationale

A useful analysis technique led us to classify, reduce and identify the

data as well as provides results that are meaningfuL Classifying gait data is an

important objective in clinical evaluations, patient rehabilitation as well as in

designing artificial limbs. But, classifying the gait panan is difficult and

complicated by the fact that gait panems vary more or less among able-bodied

subject (Laassel et aL 19% Chao 1987) and even more among patients vith a

similar diagnosis (Yamatnoto et al. 1983).

To some, able-bodied gait is the mean pattern of a large control group of

subjects having no major orthopedic or neurological disorders, which may affect

their locomotion It is o h associated to the normal gait pattern and is therefore

the gold standard with which everyone else's gait pattern is compared. While, to

others, able-bodied gait is that of a single subject rather than that of control group.

Such an able-bodied subject may exhibit large variations from the mean conml

group data making comparison either difficult or misleading. In fact, the main

difficulties encountered in performing gait analysis of gait data are data

characterization (Loslever et al. 1994).

Little is known about the homogeneity between the groups of able-bodied

subjects, <ice many axe using their own control data. The basic able-bodied gait

patterns as well as extreme cass of normality, which we should be aware of in

our interpretation of n o d gait, are presented in chapter 4.

Many gait analyses have focused on the Siomechanical aspects of the

right limb only assuming similarity with the contralateral limb. However, there

are a number of bilateral gait investigations where gait asymmetry was

documented. This is deal in chapter4. Symmetry in some recent gait studies have

been explained by a functional behavior in which one lower limb take part mostly

to propelling while other for controlling the body weight hansfommion during

the walking as given in chapter4. The functions of propulsion and cuntrol of the

lower limbs have been clearly identified during gait, but the biomechanical

parameters associated with each of them are still to be identified. The purposes of

second part of this study in chapter 4 were a) to identify the three-dimensional

peak mechanical muscle powm and the mechanical energies developed by the

lower extremities during able-bodied gait using Rincipal Component Analysis,

and b) to determine which of these gait parameters were related to propulsion and

supPo*

Most of the above studies were wrried out to confirm or reject gait

symmetry, by comparing the parameters, which influenced locomotion. There are

a few studies, which consider gait as compensation and interaction point of views.

This is describing in chapter 4.

Although gait asymmetry has been well documented, little is known about

propulsion and contrul tasks performed by each S i b and how these are managed

between them. In fact, our understanding of able-bodied locomotion improves by

studying the interaction among the many biomechanical gait descriptors (Lasko et

al. 1990.. Olney et al. 1994., Andrews et al. 1996). For the third objective we

postulate that propulsion and control functions during able-bodied walking can be

explained in part by the relationship between the gait parameters developed within

a limb and that these tasks are responsiile for the observed gait asymmetry. More

precisely, we wishto demonstrate that limb propulsion is mainly aaociated to the

i n t d o n between specific muscle power generation burs& developed throughout

the stance phase while the contralateral limb through power absorption bursts

mainly achieves wnmL Furthennore, these muscle power generation and

absorption advities are not independent but inter-limb related.

13. Structure of the thesis

Basic and essential information about gait analysis including gross

anatomy of human body, terminology used in gait studies, as well as different

type of gait measurement systems, and statistical approaches for evaluating and

malyzing gait parameters will be addressed at the first chapter. The review of the

literature based on the able-bodied gait pattems and gait symmetry is discussed in

chapter two, which able-bodied gait patterns, functional asymmetry in able

bodied gait and muscle power interaction are three papers presented in chapters

(4). A general discussion (chapter 5) will be followed at the end.

I1 - Fundamental of Gait Analysis

Human walking

Human walking is &e most common of all human movements and

consists of a repetition sequence of lower limb motions to move the body fonvard

while simultaneously maintaining stance stability. Letter and Contini (1967) have

described human and animal locomotion in three distinct stages: 1) initiation of

gait Eom rest to a constant speed 2) rhythmic gait at a constant speed and 3)

decaying stage to rest

Like most research this study will concenme on constant fke walking

speed. Before considering in detail the process of walking, anatomical terms,

bones, joiai as well as muscles as basic and essential knowledge for gait analysis

will be bricfly reviewed in the first part of this chapter. Then, movements of the

body during free speed walking which are remadably consistent (Sutherland et

al. 1994) between individuals uiU be described Furthermore, the basic events

that occur during the gait cycle and their obj- F i l y the

six determinants for an efficient gait will be shortly explained. The second

section of this chap*= deals with gait assessment including a review of the

temporal, the kintinematic and the kinetic measurement systems using passive and

active markers, ahhropometrical measurements and gait modeling. Sources of

error in gait assessment gait parametas and statistical methods will be detailed.

Section 1. Basic knowledge

Through of this section anatomical term, the gait cycle, the temporal

parameters and the gait determinants ye briefly reviewed for the benefit of these

unfamiliar while the terminology and global body motion related to human

walking.

1.1. Anatomical terms

Relationship between different parts of the body are defined in terms of

the anatomical positions, in which a person is standing erect, with the arms (palms

forward) lying at the sides ofthc body (Figure 2.1).

Fig 2.1. The anatomical positions, with respect to the three refmce planes and

six fundamental directions (Adapted h m Rose 1994).

There are three mutually perpendicular axes about which movement of a

joint could take place, although most joints can only use of these axes. The

directions of these motions are shown for the major joints of the legs in Figure

22. Some exceptions occurred in terms of definition of the movement at the

ankle and foot Plantar-flexion, dorsi-flexion, and inversion and eversion are used

instead of flexion, extension and adduction and abduction, respectively.

Furthermore, medial and lateral are used in place of internal and external

rotations.

Fig 22. Movements about the major joints of the lower limb (Adapted from

Whittle 1990).

Although it could be argued that almost every bone in the body takes

part in walking, from a practical point of view, the lower extreinities are of

foremost interest Thigh, shank, and foot are the relevant segments of lower

extranity and their comsponding joints are the hip, knee and ankle respectively.

These are shown in Figure 23.

The joints about which significant movement can take place are synovial

joints since gait analysis is generally concerned only with gross movements. In a

synovial joint, the bone ends are c o v d with d l a g e and the joint is swounded

by synovial capsule that secretes the lubricant synovial fluid. Most joints are

stabilized by ligaments that are bands of relatively elastic (elastin) and firnus

(collagen) tissues connecting one bone to another. The joint is capable of flexion,

extension, abduction, internal and extemal rotation as illustrated in Figure 23.

Fig 23. Bones and joint. of the lower limbs (Adapted from Whittle 1990).

In order to keep track of all the kinematic and kinetic parameters, the

coordinate system definition is of central importance. Location, direction or

orientation of any part of human body has to be defined by means of a reference

on global coordinate system and three anatomical planes. However, both

segments motions relative to another, three dimensional body segment motion

Chapter 2 -Fundamental of Gait A ~ b s i s If

relations to another are made in reference to the joint centers (Figure 2.4.) defined

by a local coordinate system. Thus the joint planes coincide with the global

reference in upright neutral position only while during gait the joint planes are

continuously rotated

In this study, a clocEcwise moment calculated at the distal end of a

segment is conventionally assumed positive. Thus the ankle plantar-flexion, knee

and the hip extension moments are positive. This makes intuitive sense,

especially during stance, because extensor moments accelerate the body upwards

while negative (flexor) moments will tend to collapse the body.

Such a convention have been used by a number of clinical gait

Iahratories and researhers involved in clinical analysis of gait (Cappozzo 1975..

Paul 1966.. Pedotti 1977., Rose et al. 1991.. Winter et al. 1995.. Allard et al.

1996). In the frontal plane all abductor (eversion) moments are positive and

adductor (inversion) moments are negative. In the transverse plane, external

rotation moments are labeled positive and internal rotation moments negative.

Nonetheless, there is presently a lack of uniformity in the human locomotion

literature on the specifications of the local and global coordinate systems as well

as conventions in the sense of negative and positive polarity in angular velocity,

moments and powers (Winter et al. 1995.. Eng and Winter 1995.. Allard et al.

1996). This lack of uniformity leads to ambiguities in the description of

locomotion performance.

Chapter 2 - Fwrdmnertlrrl of Gait Analysis 13

Fig 2.4. Coordinate system for lower limbs showing the global axes (Adapted

from Rose 1994).

1.2. Muscles

Muscles are responsible for movements at the joints. Most muscles are

attached at tk ends of different bones, and cross over either one joint

(monadcular muscle) or two joints @ihcular muscle). Muscles have major and

secondary zctions, which may vary according to the position of the joints,

particularly with bihcular muscles The larger and more superficial muscles are

illustrated in Figure 25. In many cases the attachment to one of the bones covers

a broad area, whereas at the othe: end it narrows into a tendon, which is attached

to the other bone.

Fig 2.5. Superficial muscles of the right leg (Adapted h m Whittle 1990).

1.3. Gait cycle definition

As the body moves forward, one l i b serves as a means of support while

the other limb is bmught forward to establish a new base. For body weight

transfer h m one limb to the other, both feet are in contact with the ground. This

series of events is repeated by each limb with reciprocal timing until the person's

destination is mched. A single sequence of these functions by one l i b is called

a gait cycle (GC). Gait cycle duration is about one second and decreases when

waking speed increases (Andriacchi et aL 1977, Grieve and Gear, 1966, Murray

et al. 1966, Rose et aL 1994).

Today, the commonly accepted convention is to describe the gait cycle

of kther limb in terms of percentage, rather than the time elapsed The events in

the gait cycle occur in a remarkably similar sequence and are relatively

independent of time, thus allowing nomralization of the data for multiple trials of

an individual subject or for a group of subjects.

The initial contact is the instant in the gait cycle when any area of the

foot initially makes contact with the ground Normally, the heel is the first area,

which makes initial wntaa, so; some times heel contact or heel-strike is used.

Therefore the initial contact of the foot @eel-strike) occurs at 0% GC and the

subsequent initial contact of the same limb completes the gait cycle at 100%.

When both limbs are simultaneously analyzed, we will present a new and

functional means of displaying their temporal relationship.

Each gait cycle is divided in two phases, namely stance and swing

(Table 2.1). During the stance phase the foot is in contact with the ground while

in swing the foot is oscillating over the ground. In the stance phase the leg

supports the body weight, advances it over the supporting leg and propels the

body forward in p r e p d o n for swing phase (IIse, 1984). It begins at I&-strike

or at the foot's initial contact and terminates at toe-off (terminal contact). Stance

can be expressed in seconds or as a percent of stride period. For natural walking,

stance takes about 60% of the GC. Howwq as walking speed increases, the

Chpfer 2 - Fwrdamental of Gail Analysis 16

pacentage oftime spent in stance denease (Craik, and Duttaa 1995).

The swing phase completes the gait cycle and begins with the foot's

terminal contact and ends at the ground contact In the swing phase, the leg

accomplishes leg advancaneat, toe clearance or leg length adjustments and

forward reach for the next floor contact. The normal duration of the swing phase

is 40% of the gait cycle.

Table 2.1. Phases and periods in the gait cycle

PERIODS RELATM PERlOl

DURATION

m~ HEEL-STRKE 15% MlDSTANCE 25% PUSH-OFF 20%

SWNG LIFT-OFF 20% REACH 20%

Able-bodied walking involves an alignment between the body and

supporting foot during stance and a selective advancement of the limb segments

in swing. This results in a series of motion panem performed by the hip, knee,

and ankle. The distance traveled by one limb b m the initial contact to the

subsequent ipsilateral initial foot contact is the stride length. Each stride consists

of five functional patterns, which called s+t periods. These are sub-phases of the

stance and swing that shown in Table 1. Each of the five gait paiods has a

functional objective and a specific motion paltan to accomplish its goal.

During the stance phase, the sequential combination of the periods also

enables the limb to accomplish three basic task. These an: heel-strike, mid-

stance, and push-off. To meet the high demands of advancing the l i b ,

preparatory posturing begins in stance. Then the limb swing to move the

nonsupporting leg forward to provide a new base of support (Hig@n$ 1995).

According to Winter (1991), swing phase's tasks can be categorized in term of lift

off and reach of the lower extremity.

In the following, those tasks will be briefly explained in terms of the

functional behavior of lower extremities. It is necessq to mention tha~ the

definition of gait periods is not consistent in the literature (Perry, 1984, 1992.

Winter, 1991).

Heel-strike is the most demanding task in the gait cycle which occurs

during the first 15% GC. It encompasses three functions namely, shock

absorption, initial l i b stability and preservation of progression Heel-strike

occurs between the foot initial contact and the time of maximum knee flexion,

about 15 degree of the supporting limb. The challenge is the abrupt transfer of the

body weight onto a limb that has just finished swinging fonvard and which has an

Chapter 2 - Fundamendof Gail Analysis 18

unnable alignment If the contact is made simultaneously by the heel and the

heads metatad, then foot fiat is the same as initial contact For certain

patho1ogical gait when knee flexion does not occur, weight acceptance is defined

as the time between initial contact of the ipsilateral limb and toe-off of the contra

lateral l i b .

The period determined by maximum knee flexion and heel-off d e h e

mid-stance. It occurs between 15% and 40% of the GC. During this interval, one

l i b has the total responsibility for supporting body weight in both sagittal and

coronal plane while pmgression must be continued.

Push-off begins of heel-off as it pushes away from the ground and ankle

plantar-flexion occurs. In other word, push-off is dehed as the period in time

when plantar-flexors contract concentrically to produce major generation energy.

Push-off ends at toe-off and occurs between 40% to 60% GC.

13.4. L i i off

It begins with toe-off where the lifi-off from the floor and ends when the

swinging foot is opposite the stance foot and covers 20% GC or halfof the swing

phase duration The main objective is to advancement and foot clearance h m the

floor.

13.5. Reach

Reach is the period of time during swing which begins with a knee

extension, and ends when the foot strikes the floor and complete the A n i n g

20% GC. L i b advancement is completed as the leg (shank) moves ahead of the

thigh The objectives are to complete limb advancement and to prepare the limb

for stance.

1.4. Temporal parameters

Speed, 6 d e length, and cadence as the global gait parameters describe

the overall function of gait This section will provide commonly used operational

definition Walking speed is the measurement of distance per unit time.

Typically, average walking speed is expressed in meters per second (mls). The

average speed reported in labomtory condition using different method is 1.34 mls.

It is illustrated in Table 2. Munay (1964,1967,1967) reported a mean velocity of

152 rnk for 60, 30, and 50 subjects, rrspectively. While, Winter et al, (1974).

and Eng and Wmter (1995) reported a mean velocity of 126 +I- 0.12 mls and 1.6

Chapter 2 - Funainnental of Gnir A d y s i s '0

+I- 02 mk for 12 and 9 able bodied subjects respectively. In this study, average

velocity for 57 trails was 130 +I- 0.12 ds. This value corresponded to those

reported by Grail (1995) and Oberg et al. (1993) for natural walking. In general

as walking speed changes, the foot falls patterns change. Therefore, the foot

contact pattern are considered speed dependent (Cd and Duttem 1995).

Step length is defined by the distance between two consecutive

contralateral contacts of the lower extremities with the ground Thus there are

two step lengths, a right and a l e 4 within one stride. The distance h m initial

contact of the left foot to initial contact of the right foot is a right step length and a

temporal parameter associated with step length is step time. Thus, if gait is

symmetrical the left and right steps are equal.

Stride length is defined by the linear distance h m a contact event of one

foot to the subsequent contact event of the same foot with the ground. Therefore

one stride equals one complete gait cycle and composed of one right and one left

step length.

It is evident that sped that is the distance covered by the whole body in

a given time in a particular direction is dependent of stride length and cadence.

Stride length and cadence - the number of gait cycles of both legs per time unit-

are dependent on each other. Lamoreux (1971) summarized the result of his work

along with those four others and noted that between cadences of 80 and 120,

stride length and cadence each varied as the square root of the speed. Murray

(1964, 1967. and 1969) qor ted similar results. Thus, up to a cadence of 120,

speed increases arc achieved equally by increasing stride length and cadence.

Above 120, step length, levels offand cadence only increases (Wi 1991).

Nahual cadence reported in the literaii from 101 to 122; our laboratory

has recorded 19 normal subjects (mainly university students, aged 25-35) which

have a cadence of 1072 +/- 7.51 (Sadeghi a aL, 1997). Drillis, (1958,1961) for

936 and 752 pedesaians reported a mean cadence of 112, varying from 79 to 135,

while Finely reported 116.4. Furthermoq Winter (1991) and Eng and Winter

(1995) reported a mean cadence of 107 +/- 8.8 and 108 +I- 10 for 60 and 9 young

adults' subjects, respectively. A cadence varying h e e n 100 and 122 steps per

minute had been reported by Grail (1995) and Oberg et al. (1993).

It should be emphasiued that the above parameters of the human gait are

Comparable only when limited to 6r.e speed walking on level ground. Age-

matched normal controls are also required when comparing children or older

adults.

Introducing other variables such as, gender can also change these

relationships. For example, Du Chatinier et aL (1970) revealed that females

walked slightly more rapidly than males with values of 116 and 122 steplmin for

a population of 72 males and 57 females, respectively. Mean while, Molen and

Romdal (1972) reported for about 500 young adults that the male cadence

averaged 113 compared to 124 for females Therefore, we can conclude that

female natural cadence is 6 to 11 steps/min higher than that of males.

Table 22 Global gait parameter with their standard deviations (SD) for able-

bodied, male subjects

Double support is defined as the time when the stance phase of one limb

overlaps the stance phase of the contralateral Sib. There is a period time in

which both feet are in contact with the ground. Double support is therefore the

difference in time spent befween in the stance and the swing phase. It was

estimated to vary !?om 16% to 22% and if perfect symmetry is assumed, this

would consist oftwo double support time of 8% to 11% per stride (Winter. 1991).

Chapter 2 - FvndmnorroI of Gad A d y s i r 23

Double support periods ye also defined as double suppon right and let?

according to the corresponding initial contact. On the right side the double

support right appears lirst and vice vma. For consistency reasons the two plmes

ye referred to as initial double support and taminal double suppon for each l i b .

1.5. Locomotion functions

Since, the results of this study conducted on gait asymmetry is explained

in term of forward progression and control as the two main tasks of lower

extremities, the meaning of a safe and efficient propulsion is important to

understand. According to the liter- detailed below, five main functions must

be performed &&g each gait cycle. The-y are as follows,

a) Maintenance of suppon of the uppa body (i.e. prevent collapse

of the lower limb) during stance (Wiiter, 1980,1984, Perry,

1992, Patla, 1991).

b) Maintenance of upright posture and balance of the total body

(Nashner, 1980, 1982, Cappozo, 1981, Thorstensson, 1984,

Wmter, 1987, Patla, 1991).

c) Control of foot trajectory to achieve safe ground clearance and a

gentle heel or toe landing (Wiiter, 1982, Perry, 1992).

d) Generation of mechanical energy to maintain or to increase the

forward speed (Wimter, 1983a 1985b, Peny, 1992, P a t 4

1991).

e) Absorption of mechanical energy for shock absorption and

stability or to decrease the forward velocity of the body

(Wiiter, 1983a, 1983b,Perry, 1992).

All of the above hctions must be performed within the anatomical

constraints of the human body. These constraints summarized by Saunders,

Inman and Elberhart (1953) to six determinants of gait.

1.5.1. Gait determinants

The brief description ofthe six determinants ofgait will be given here.

15.1.1 Pelvis rotation:

The first determinant of gait is the way in which the pelvis rotates about a

transverse axis alternately to the right and to the left, relative to the lime of

progression At the customary cadence and stride of typical people, the

magnitude of this rotation is approximately 4 degree on either side of the central

axis, or a total of some 8 degrees. This value usually increases markedly when

speed is increased. Because the pelvis is a rigid structure, the rotations occur

alternately at each hip, bringing the pelvis forwards as the hip flexes and

backwards as it extends. This mcms that for a given stride length. less flexion

and extension of the hip is required, since a proportion of the stride length comes

from the f o d and backward movement of the pelvis rather than the angular

movement of the leg.

However, with the leg vertical and the foot on the ground, any flexion or

extension at the pelvis will not only move the trunk backward or forwards. but

will also lower its vertical height. The longer the stride length, the greater the

angle of flexion and extension of the hip, and the more the trunk loses height

(Figure 2.6).

Moved forwards by ! I pelvic rotation

Hipw; izw Leg

Fig 2.6. F i determinant of gait: pelvis rotation reduces the angle of the hip

flexion and extension, which in hlm reduce the vertical movement of the hip

(Adapted from Whittle 1990).

1.5.1.2. Pelvis tilt:

As described above, flexion and extension of a rise and fall in the height

of the hip accompany the hip. If the pelvis was to keep level, the trunk would

Chapter 2 -Fundamental of Gait A ~ I p v i r 26

follow this up and down movement However, the second determinant of g6t is

the way in which the pelvis tilts fium side to side, so that when the hip of the

m c e phase leg is at its highest point, the pelvis is inclined, to lower the hip of

the swing phase leg. At moderate speeds, the alternate angular displacement is

about 5 degrees. The displacement occurs at the hip, producing an equivalent

relative adduction of the supporting limb and relative abduction of the other limb,

which is in the swing phase of the gait cycle. The height of the trunk depends not

on the height of one or other hip but on the average of the two of them, so the

pelvis tilt reduces the total vertical excursion of the hunk (Figure 2.7). This

pelvis tilt can only be achieved if the swing phase leg can be shortened

sufficiently (normally by flexing the h e e and domi flexing the ankle) to clear the

ground.

support stance support

Fig 2.7. Second determinant of gait The vertical movement of the center of

mass is less than that of the hip, due to pelvis tilt (Adapted fium Whittle 1990).

15.13. Knee flexion in stance phase:

The third to the fifth determinants of gait (Figure 28) all concern the

adjustment of the effective length of the leg during the stance phase, to keep the

hip height as constant as possible. The third determinant is the knee flexion of the

supporting limb as the body passes over it during stance phase. This supporting

member enters the stance phase at heel-strike with the knee in nearly N 1

extension In fact, as the thigh passes fbm flexia of the hip into extension, the

hip would rise and then fall if the leg remained straight However, flexion of the

knee shortens the leg in the middle of this movement, reducing the height of the

apes of the curve.

15.1.4. AnWe mechanism:

Complementary to the way in which the apex of the curve is reduced by

shortening the leg in the middle of the stance fbm hip flexion to extension, the

beginning of the center of mass displacement curve is elevated by lengthening the

leg at the time of heel contact This is achieved by the fourth detQminant of gait -

the ankle mechanism. Because the heel sticks out behind the ankle, it effectively

lengthens the leg during the period between heel contact and foot fld (Figure 2.8).

15.15. Foot mechanism:

In the same way that the heel lengthens the leg at the beginning of the

stance phase, the forefoot lengthens it at the end. This is the fifth determinant -

the terminal rocker. Fmm the time of heel-OK the effective length of the lower

leg increases as the ankle moves from dorsi-flexion into plantar flexion (Figure

2.8).

Hecl Stancc Hccl Toe contact phase OH off

kncc iicLon

Fig 2.8. Third, fourth and fifth determinants of gait Stance phase, knee flexion

shortens the leg (third); the heel lengthens it (fourth); so does the forefoot (fifth)

(Adapted from Whittle 1990).

15.1.6. Lateral displacement of body:

The fm five determinants of gait all concern the reduction of the vertical

excursicns of the center of mass. The sixth is concerned with side to side

movement By keeping the walking base narrow, little l a t d movement is

needed to preserve balance during walking (Figure 9). The reduction in l a l d

acceleration and deceleration leads to a reduction in the use of muscular energy

(MacKinnon and Whter 1993). The main adaptation, which allows the walking

Chapter 2 - Funuhenfal of Gzi! A+ 29

base to be narrow, is due to a slight valgus angulation of the knee, which permits

the tiiia to be vedcal while the femur is angplated to be slightly adducted.

It is obvious that although the six determinants of gait have been described

separately. they are integrated together during each gait cycle. The combined

effect is a much smoother trajectory for the center of mass, and a much reduced

energy expenditure, than would have been the case without them. Furthermore,

reference has already been made to the rotations of the pelvis that occur during

walking. These rotations are easily seen when anention is called to them. There

are also the rotations of the thorax and shoulder, thigh and leg, as well as ankle

and foot, (Rose et al., 1994) involving the part of the body above and below the

pelvis, that Saunder et al. did not mentioned them.

In summary, the major angular displacements of the body during

walking have been presented based on the observation of normal gait The six

determinants of the gait were used to minimize the excursions of the center of

mass Pelvis rotation (m the horizontal plane), pelvis tilt or list (above or below

the horizontal plane), and stance phase knee flexion-extension are three

determinants that act to flatten the trajectory of the center of mass of the body

when compared with a stiff-legged, compass gait

The interadion of foot and knee mechanics during stance (two

additional determinants) helps to provide a smooth transition of the trajectory of

the center of mass. They describe the constraints of the interconnected

segments and therefore establish the anatomical framework and limits within

Chaprer 2 - FvndcuMntnl of Gait Anal)sis 30

which the n~omuscular system must o w e .

Fig 2.9. Sixth determinant of gait: having the feet closer together reduces the side-

to-side movement of he center of gravity necessary to maintain balance (Adapted

fium Whittle 1990).

Section 2. Gait assessment

Many biomechanical three-dimensional analyses of human movement

begin with data capture using an imaging device. Advances in bioengineering and

computer technology have enhanced the sophistication and reliability of

inshumentation, improved the speed and storage of data acquisition, and

automated the process of data reduction (Dimnet et al. 1996).

Current technology pennits dynamic recording of many specific gait

characteristics such as the displacements of the body, step length, stride, joint

an@% angular velocities, and angular accelmtion, p u n d reaction forces, joint

forces, moments, and powers, as well as electmmyography (EMG) activity, and

Chapter 2 - F W of Gait Analysis 31

energy consumption

In this study, able-bodied gait panern, functional gait symmeay have been

investigated in term of simultaneous, 3-D, temporal pGuameters, peak mechanical

muscle powers and their associated energies developed at the hip, knee, and d e

using a video-based with passive markers.

2.1. Temporal and spatial measurement systems.

Temporal and spatial parametm include the recording of waking speed,

step and stride lengths, etc. Their measurement offers an important insight into

normal and pathological walking panems Furthermore, collection of footfall

parameters accompanied by the data on neuromuscular integity and physical

activity level. This may yield results that suggest avenues for measuring and

analyzing additional kinematic and b e t i c variables to provide insight into the

mechanisms responsible for the production of walking. Although measuring

temporal and spatial parameters in gait analysis are necessaries, these parameters

alone are not sufficient for appropriate analysis and full assessment of human gait.

Temporal and spatial parameters can be recorded with very basic

equipment such as stopwatch with a marked walkway and powder on the feet

They also can be measured by some more complicate equipment such as foot

switches combined with a microcomputer-based system as well as with opto-

electronic systems.

In this study, the temporal and phasic gait parametas were determined

from the force plate and video data. Initial contact and toe-off were determined

from the vertical p m d reaction force while the ipsilateral subsequent heel-strike

was determined from video data. Stance and swing phases, step and stride length

as well as double support were obtained from initial contact and toe-off

measurements Funhemore, breaking, push-ofX and speed were calculated by

means of the anterior and posterior force patterns and hip displacement

respectively during the gait cycle.

2.2. Kinematic measurement systems

Human gait assessment involves hacking the movements of the body

segments as the subject moves throughout space. Kinematic systems are used to

record the position of the body segments and calculate their comsponding linear

and angular velocities and accelerations. Goniometas measure joint angie

changes (Chao, E.Y. 1980). Various type of goniometas are available. for

example, electrogoniometm (Jhonson, and Smidt, 1969), polarized light

goniometas (Mitchelson 1977) and flexile goniometas (Penny & Giles Gwen,

UK). They are relatively inexpensive and simple to use and provide an instant

result However, there are some disadvantages in using them. The time to

calibrate the equipment, interference with gait, single joint angle information and

the alignment of the device with the human joints are hut a few examples of their

limitations.

Accelerometers also could be used to measure the kinematic variables.

Accelerometers are small and lightweight precision tmwducers. However these

types of accelerometers are usually uniaxial and more than one is required to

obtain information in diffkent planes (Monis 1973). Furthermore, they are

expensive and the subject is anached to a hailing wire.

Cinephotography was also used in early gait analysis systems. They

used motion picture film to capture real time events for analysis. Markers such as

wooden sticks mounted on the pelvis and tibial belt were used to help idenefy

movement of body segments. Cinephotography was the principal technique for

gathering kinematic data (Murray et al. 1964, Inman et al 1980) before the

introduction of opto-electronic systems.

The three-dimensional marker position can be quantitatively determined

using two or more cameras. It would be done by manually digitizing the location

of a marker placed over anatomic landmarks on a h e - b y - h e basis

(Sutherland 1994., Hagy, 1972). While this technique may be suitable for

research purposes it is unsuitable for routine clinical use hccause manual

digitidon is time expensive and requires a fmined operator (Sutherland 19%

Davis, 1988).

Today, computer and image processing technology has advanced, more

automated data acquisition procedures have been developed. Video based

systems e l i t e the need for processing film and have an additional advantage

ChavIer 2 - Funahend of Gait A& 34

becarrse the signal is electronic. The video signal can be recorded on magnetic

tape or converted to digital information

Today, video-based systems such as those of Motion Analysis

Corporation, Peak Paformance, Selspot, Oxford Metries Ltb, and Northern

Digital are interfaced with a computer to overcome the disadvantages of

Ciephotogaphy. They are sophisticated instnunents using multi-camera video

information for threedimensional motion analyses (Figure 210).

However it has to be remember that, in all above-mentioned methods,

operator assistance is needed to process the raw data and obtain results after data

collection A wide range of software is available for 2D or 3D reconstruction of

stick figures and force veaors In addition to positional information, they can

acquire and pnxra force plate data simulbneously. Different of markers

and camera arr used by the various systems that are available. Some of the

currently available opto-electronic systems are dkcused briefly below.

22.1. Active marker systems

Active marker commercial (optoelectsic) synen-n include Selspot.

Northem Digital. In these systems, light emitting diodes (LED) are pulsed at a

predetermined frequency. The active LED markers are pulsed sequentially &om

the controlling unit providing the computer with automatic identification of

makers.

The active marker systems offer the advantags of high sampling ra t s

(200 to 300 Hz). But, as the number of active markers increases the sampling rate

is reduced. Furthermore, the use of active markers requires trailing wires for

power and control and this could make them unsuitable for the analysis of fast

movements such as running and jumping as well as for subjects having

locomotion impairments.

Selspot uses up to 16 cameras (telemetric or hardwired) with LED

markers attached over the anatomical landmarks, a signal processing unit and a

controlling computer. Northem Digital uses up to four cameras and offers a very

rapid camera-sampling rate of 4700 markersls/camera. A maximum of eight

markers can be used to each power distributor.

23.2. Passive marker systems

Sane of the passive marker systems currently available include Ariel

Oxford Metrics Ltd., Peak Performance, United Technologig Motion Analysis

Corporation. The following explanation focuses on video based system with

passive markers, since in this study, data optme was performed by means of a

Motion Analysis System (Expert Vision). Although standard video technology

allows sampling at 50 or 60 Hz, 200 to 2000 Hz Systems are available for high-

speed analysis in sport applications ( G m v g J.OB 1994). The video signal can

be raorded on magnetic tape or converted to digital information. Computer

technology has provided the means to process more digital information at faster

rates for lower coA

In all the video based systems including Motion Analysis System,

passive markers are made h m highly nflective material and appears very bright

to a camera when a light close to or surrounding the camem lens is projeaed on

them. System using passive markers, present the advantages of not requiring

subject wiring or power supplies (Pedoni and Fenigno 1994). but they require an

illumination sources (typically visible or infrared light to minimize subject

d i d o n ) . Furthermore, they have a high flexibility in terms of experimental

set-up. Also the surveyed picture is visible on a monitor together with recognized

markers and this ass- the possiiility of re-trailing the experimental set-up on-

line or in the field (Pedotti and Fenigno 1994). If single markers are used, three

markers must be placed on each limb segment to cany out a 3-D analysis

however, adjacent segments can share a joint marker.

Passive marker systems have their own software package and hardware

characteristics for data processing and analysis. Many of these systems offer

optional features including marker data filtering, generation of stick figures,

analysis of joint velocities, determination of joint moments and powers, and

graphical clinical presentation of the resulting data They often allow the user to

access the dam files for their own analysis or application

The 3-D coordinates of the c e n d of each marker are calculated by

combining two views of the same marker from synchronized cameras. An

operator enters a label for each marker, such as the fifth metatarsal, heel and so

forth, in one &me of the video. Computer software nacks that patticular marker

and identifies it in all of the other frames. The operator must also specify how the

markers are to be linked to define a stick figure that represents the body segments

and the joint centers of rotation These processes replace the need for digitizing

each frame of cinefilm manually.

The trajectory of the limb segment in space is calculated relative to the

reference coordinates defined during the calibration procedure. The relative joint

angles between the limb segments can then be computed. The angles must be

expressed as a change from Zen, or n e u d position. The motions are assigned to

changes in positive and negative directions are controversial subject and will viuy

between laboratories.

The coordinates of markers are calculated from the image markers using

a stereo reconstruction technique originally designed for aerial photogrameey.

The Direct Linear Transformation (DLT) technique developed by Marran (1975)

is one of the popular tlmedhensional reconstruction methods in biomechanics

(Gmen 1996, Stokes et al. 1987.. Nard et al., 1987.. Shapiro, 1978, Leroux et

al. 1990). The DLT method is based on the classical technique and represents a

3-D object space h m 2-D images by:

where u and v are the image coordinates and Au and Av are the image coordinate

correction for lens diiortion The object point coordinates are X, Y, and Z while

the constants L1 to L11 are the DLT parameters which define the camera position

and orientation as well as the camera internal parameters and lirear lens distortion

faors. Wlth the DLT equations, the camem can converge but care must be

taken so that the relationship between the convergence and the overlap angles

defined in Manan (1975) is respected to minimize the recoNtruction error. This

is not always possible in a laboratory environment and a compromise between

camera setting and an acceptable error must be reached. Sources of errors and

their influence on the quality of reconstructed coordinates will be discussed in

section 2.6.

The path of each limb segment in frontal, transvase, or sagittal planes

can be plotted as a function of time. l'here are usually artifaas produced by the

digitizing pmcess or movement of the marker on the skin which do not reflect the

change in position of the limb segment These curves may be smoothed with a

digital filter that removes high fkquency changes, which could effect the result of

calculating the velocities and accelaatious. W i e r (1974, 1991) has determined

the harmonic content of the trajectories of seven leg and foot markers during

human normal walking. He documented the highest harmonics to be in toe and

heel trajectories as 99.7% of the signal power. It was contained in the lower

seven harmonics, which is below 6 Hz

Recent technological advances in digital filtering have opened up a much

more promising and less restrictive solution to the noise reduction The basic

approach u n be d e s c r i i by analyzing the fkquency spectrum of both signal

and noise. Figure 2.1 1(a) shows a schematic plot of a signal and noise spectrum.

As can be seen, the signal is assumed to occupy the lower end of the fkquency

spectrum and overlaps with the noise, which is usually higher fiquency.

Fig 2.1 1 (a). The spectrum of a signal with additive noise )(Adapted h m Wmter

1995).

Chapter 2 - Fundmentol of CairAnalysis 40

The theory behind the digital filtering (Radar and Gold, 1967) will not

be covered, but the application of low-pass filtering, which has been used in this

study, will be briefly discussed Filtering of any signal is aimed at the selective

rejection, or attenuation, of certain fi-equencies. In the above case, the obvious

filter is one that passes the lower frequency noise. Such a filter called a low pass

filter and has a frequency response as shown in Figure 2.1 1 (b).

Fig 2.1 I@). Response of low-pass filter introduced to reduce the noise (Adapted

h m Winter 1995).

The frequency response of the filter is the ratio of the output X*(f) of the

filter to its input Xi(Q at each hquency present The response at lower

hquencies is 1.0. This means that the input signal passes through the filter

unattenuated. However, there is a sharp transition at the cutoff fi-equency (Fc) so

that the signal above Fc are severely attenuated. The net result of the filtering

process can be seen by plotting the spectrum of the output signal X(Q, as seen in

Figure 2.1 1 0. Two things should be noted. First, the higher hquency noise has

been severely reduced but not completely Second, the signal, especially

in the region where the signal and noise overlap is also slightly attenuated.

Fig 2.11 Q. Spectrum of the output waveform after filtering (Adapted from

Winter 1995).

The order of the filter decides the sharpness of the cutoff. The higher the

order, the sharper the cutoff. In this study Butterworth-type low pass filter of

second order was used

Tracking the markers on the foot provides the necessary information to

calculate stride dimensions. Simultaneous measurements of the rotations

occurring in each segment enable the examiner to observe individual kinematic

parameters or combined patterns of motions that are difficult to assess visually.

These data are important to relate the motions to the events of the gait cycle. The

motion data may be combined with analog data such as force measurements.

In summary, recent technical advances have made optoelectronic based

systems almost standard for the recording of body segment 3-D movements and

the generalid availability of digital computers have nmarkably enhanced the

C'haprer 2 - Fundamentor of Gaif Analysis 42

possibility of making sophisticated motion analysis. Now, it is possible to

sample analog data at higher a e s and w more sophisticated filtering and

smoothing techniques

Trends towards higher speeds and lower costs of computers, together

with hardware and software developments for marker detection and tracking,

means that, probably, the passive marker and addressable video camera

combination will be the future standard in this field. 3-D measurements of

human movement are reduced to the detection of the trajectories of several points

which identify the positions of the body segments in space.

Instrumental analysis is useful for detecting and recording locomotion

events that can not be observed by clinician, or researcher, including forces, and

motions too small or rapid to detect by eye. The necessary measurements can be

completed in a practical amount of t h e with minimal interference to the natural

movements of the subject

23. Kinetic measurement systems

Kinetics is the part of mechanics that deals with the study of forces and

the way they affect motion of objects and systems (Seliktar, Bo 1995). In order to

measure the force exerted by the body on an external body or load, using a

suitable force-measuring device is essential. Such a device, called a force

transducer, gives an elecbical signal proportional to the applied force (Winter

Chapter 2 - Fundnmenral of Gait AnaljJir

1991). There are many h d s available: strain gauge, piemresistive transducm

capacitive devices, and others. All these work on the principal that the applied

force causes a ceaain amount of strain within the transducer.

The foot-floor ground reaction forces widely measured by platform have

been developed by manufaaures using strain gauge (AMTI) and piezoresistive

transducers (Kistler). These systems measure forces in three orthogonal

directions (one vertical and two horizontals) as well as the center of pressure,

which is the point of application of the ground reaction force on the foot.

However, force plate data by themselves have one major Sitation. If more than

one foot strikes the force plate, the data annot be used to separate out the

contribution of each foot But, force plate analysis is most usel l measurement

when combined to a three-dimensional motion analysis system.

Newton's second law of motion is used to estimate the forces the

muscles must produce to generate motion Investigation of the relationship

between factors causing motion such as forces and torque and the motion itself

defines the area of study called dynamics or kinetics (Hanis, et al. 1994). At each

joint, a state of equilibrium exists such that the internal joint forces and moments

generated by muscles, ligaments, and bony structure balance the externally

applied forces. (Seireg and Arvikar 1975). The Newton-Euler equations of

motion can be applied at the joint to determine the muscle contriiution (Gage,

1989.. Winter, 1990., Vaughan a al. 1992).

Gait analysis includes not only kinematic but also kinetic data such as

ChopIer 2 - Fundanendof Gait Analysis

hip, knee, and ankle joint muscle moments. Moments can give insight into subtle

musculoskeletal adaptations such as the increased flexion moment seen at the hip

and knee in the anterior m i a t e ligamentdeficient patient (Andrimhi et aL

1985). Preoperative knee adductor moments have been suggested as predictors of

postoperative clinical results fium high tiiid osteotomy (Prodromos et al. 1985).

Joint moments can also be usell for clinical decision making in cerebral palsy

(Lai et al. 1988).

2.4. Anthropometry measurements

Anthropometry, a major branch of anthropology, is the science used to

describe human body by its dimension, mass and mass distribution (Heymsfield

et al. 1987.. Rodgers et al. 1984). Many of the earlier anatomical studies

involving body mass and limb measurements were not considered to be of interest

to biomechanics ('Winter 1990). However, it is impossible to develop a

biomechanical model without knowing the masse of limb segments, the location

of mass centers, the segment lengths, the center of rotation the moment of inertia,

and so o n In other words, the accuracy of any analysis depends as much on the

quality and completeness of the anthropom&c measures as on the kinematic and

kinetic data (Wmter, 1990).

There are various approaches to estimate the body segment parametas

for a particular subject such as geometrical shapes (Hanavan 1964, Hake 1980),

UIIlpter 2 - F u n u k a d o f Gait Analysis I S

scanning technique (Brook a al. 1975, Redmann 1989, 1976, Martin et al.

1989.. Zatisorosky et al. 1985). cadaver average ( B m e 8: Fischer, 1S89..

Dempster, 1955.. Dempster et al.1959). reaction board (Banstein, 1967).

mathematics modeling (Hamvan, 1964, Hatze, 1980)., kinematic measurements

(Ackland, Blankksby, Bloomlield. 1988.. Dainis 1980, Vaughan and Hay 1982).

In present study, Dempster et al. (1955, 1959) data was used. This

technique based on the cadaver avmge provides estimates of segment length and

joint center locations relative to anatomical landmarks.

2.5. Gait Models

Characterization of joint motion in terms of anatomical planes requires

that motion be expressed in terms of orientation about three orthogonal axes.

Classically, Euler angles are the most commonly used method to provide this 3D

joint representation (Chao 1980, Ramalaishman et al. 1991, Grood and Suntay

1983). This is a technique of describ'ig the orientation of one coordinate system

relative to another. Three angles are described, each associated in order with a

rotation of the moving coordinate system (distal body segment) with q e c t to a

reference coordinate system (proximal body segment or the laboratory). Three

coordinates (X, Y, and Z) give the positions of the segment's center of mass and

the rotation to orient i t The first rotation is about the sagittal, then the mronal

and last by the tmnsvexse axis which are showed in Figure 2.12.

Fig 2.12. The three an& degrees of M o m (or Eder angles) defining the

orientation of a segment's refrence axes relative to the global reference system

XYZ (Adapted from Vaughan 1992).

One of the goals in assessing locomotion is to estimate the joint reaction

forces and muscle moments. As pointed out by Vaughan, Hay, and Andrew

(1982). there are essentially two types of approaches to obtain this information

using rigid body dynamics, namely, the D m and Inverse Dynamic problems.

In direct dynamic analysis, the forces being applied to a mechanical

system are known and the objective is to determine the motion that results

(laughan et al. 1992). In gened, the experiment is performed on a computer

model instead of on a human subject, to analyze internal forces for certain types

of human movement. This is analogous to the common practice in mechanical

engineaing, especially in robotics and vehicle dynamics, where new designs are

Chapter 2 - Fwrdnmenrol of Gait Analjsis 47

tested by computer simulation before building a first prototype.

The entire model, muscles and body segments are represented by a large

set of coupled differential equations. Simulations of movement are accomplished

by simultaneous numerical solution of these equations. Forces in all anatomid

structures included in the model a~ obtained as a product of the simulation.

The direct measurement of the forces and moments transmitted by

human joints, the tension in muscle groups. and the activation of the peripheral

and central nervous systems are fraught with methodological problems (Vaughan

et al. 1992.. S e l i and Bo 1995). That is why gait analysis adopted the indirect

or inverse approach Inverse dynamics is the most widely used method for

estimating internal loads.

The term inverse dynamics refers to the fact that forces are inferred h m

the movements. This method involves substitution of measured motion data, to

obtain the forces responsible for the motion This is opposite to the direct

solution method. Inverse dynamic is based on a representation of the human

body as a set of rigid segments (Winter 1990., Vaughan 1992).

Some l i tat ions of the inverse dynamic solution are due to the

separation of resultant loads into the individual forces in muscles and other

structures such as tendon, ligament and atticular surface. Unfortunately, a large

number of unknown faaors are involved, especially in the internal moment

generated by the different muscles, and in the extent of any simultaneous

contraction by antagonists (Whittle 1991).

Invase dynamics also relies heavily on the assumption that body

segments are rigid The errors cawed by this simplification are m9a severe in

impact and vibration shldies (Boggat 1994). For these reasons, such calculation

can only be approximate, but they can be extremely valuable and are very a

powerful tool in gaining insight into the net summation of all muscle activity at

each joint (Wmter 1991.. Vaughan et al. 1992, Whittle 1991).

2.6. Sources of error

The intend of my measuranent is to capture the true nature of an

observable phenomenon However, each measurement has an associated error

making it more or less inaccurate. So far, many attempts have been made to

reduce the errors. In general, some errors are correlated with the process under

investigation for example, the rigid-body model that ignores all soft-issue

deformation during movement. Another example of essentially independent

errors is wide-band measurement noise in opto-electronic equipment for 3-D

kinematics. It might appear that there is no need to reduce wide-band

measurement noise because of the limitation of the rigid-body model. While this

is true to some extenb different m r types may have different effects on the

variables being estimated. In particular, wide-band 'white' measurement noise

has a deleterious effect on estimated derivatives, while model ahfaas may have

more influence on the smoothed data at low hquencies (Woltring 1994).

To m h h h sources of m r , an accmate method of camera and system

calibration is needed. By using marker placed at known location in the

laboratory, the accuracy of the system can be described in tams of a percentage

of the !mown separation distance. The system resolution describes the ability to

. . . d m u m a t e position in terms of a lmear measure and should be defined with

reference to the volume within the data q u i d System calibration typiully

conducted on a daily basis is used to correct for changes in system characteristics

due to camera placement, temperature change and sensor and electronic drift.

In both active and passive marker systemg the location of the markers

with respect to anatomical landmarks is critical to the overall accuracy of the

system. Marker sources of error include incorrect placement with respect to the

anatomy, skin and soft tissue motion, marker dropout b r n l i b swing or

assertive device, tmnk rotation, and marker vibration (Kadaba et al. 1989, 1990,

Davis 1992, Vaughan 1992, Sussman i993). Marker set designs attempt to

maximize the distance between markers to prevent image overlap and sorting

difficulties. A resulting shortcoming is that small body segments such as the feet

of children can not always be fully identified or kinematically modeled.

Solidification procedure developed by C h k et al. (1995) is a proper way for

reducing one of the major sources of kinematic error. The advantage of applying

such a technique is to increase accuracy of three-dimensional kinematic

calculation.

It is necessary to note that, the amount of error, movement of skin

Chapter 2 - Fundnmaful of Gai~ Analysis 50

marker, in final result depends on which parameter is being measured. For

example, marker movement has little effect on the sagittal plane knee angle,

because it causes only small relative change in the lengh of segments, but it may

muse considerable ma in transverse plane measurements involving shorter

segments, such as the foot (Whittle 1991).

?he data collection procedures used to obtain the ground reaction forces

can introduce errors in a quantitative analysis. In kinetic gait models, potential

sources of error include any kinematic errors due to marker placement, and

required estimates of anthropometric characteristics such as segment mass, center

of mass, and mass moments of inertia However, force platforms are usually

placed in the walkway and covered or othenvise concealed so that the subject is

unaware of their locations. This is done to pnvent the subject 6-om targeting

leading to changes in step dimensions so the foot will land on the plate.

Nonetheless, if the platform is not in view, it may be difficult to get the subject to

step on the force plate at all.

In short, awareness and elimination of errors which can influence the

measurements and the anal* have to be taken in account h m beginning of

data collection up to the results.

2.7. Gait parameters

In general, the hdamental information used in the analysis of human

gait is composed of motion, which are displacement and its derivatives. They

give us some global idomation about velocity (Peny et al. 1993., Olney et al.

1994). stride length (Wooten et al. 1990., lohamon et al. 1994). cadence (Wooten

et al. 1990.. Winter, 1992), single support time (Skinner and Effency 1985), step

length (Winter, 1992, McCaws, 1992).

Furthermore, motion variables and ground reaction forces provide the

basic infomation needed to compute the moments exerted about the joints and in

turn facilitate the computation of the internal joint foxes and muscles'

contractions (Lehman et al. 1987., Wooten et al. 1990, Seliktar, Bo 1995).

Kinetic analyses allow us to calculate the energy developed in the limb during

movement. The kinetic and potential energies of each segment and the total

energy are calculated along with the mechanical power generated, absorbed and

transferred by the muscles at each joint (Winter 1975,1976., Lehman et al. 1993..

Allard et al. 1996.. Sadeghi et al.1997). More precisely, muscle mechanical

power is one of the variables, which reveals the functional role of the anatomical

structures and the cause of movement

An integration of the area under each phase of the power curves yields

the work done by the muscles (Colbome et al. 1994.. Allard et al. 1996.. Sadeghi

et al.1997). Tie integral of each power phase (i.e. work) as a variable having a

single value will be complete our data analysis. Negative work represents energy

absorbed during critical phases of the gait cycle (i.e. absorption by the quadriceps

just after heel contact to prevent knee collapse). Positive work indicates the

phases where energy is generated to maintain or increased speed such as

generation of the plantar-flexors during push-off to add energy to the lower l i b

prior to the start of swing Power generation, absorption and transfer in different

situations in tam of type of the movement are well ' A by Robertson

acd Wmter 1980. This is illmtmted in Table 23.

This result in a large number of parameters, nwking interpretation of gait data

extremely difficult So, in making aa assessment of gait one has to determine

which parameter(s) are important

Table 23. Power generation, absorption and transfer functions in the lower

extremities (Adapted from Winter and Eng 1995).

Both upnml. NIUlng In wrrr dimsrion

(a) Psn: mgk dwrcrGng (F.c.. ", > Yl

(b) joinl ungle inrrcmmg (c.& -2 ' ",)

Ore xemcnl fixed (F.L.. V-I I )

(a) joint mf lc denrinmg (w, r 0: *>O)

(b) jomt rnelc mcmarmg (w, r 0: w:>o,

(Cl p i n t rngk NII.Wt (", . * - 0 )

Mu, ahwrbcd frnm Y&Ynmll

Mu, ~.bsc.bd from vgmcnl 2

Mo, i""dCmJ 10 ug-1 I fmm 2

UlopraZ - Fwuknnsrtal of Gait Anolysir 53

In short, though temporal and phasic gait parameters, joint angles and

muscle moments may be used to charaaerize gait pattans, muscle powers are

more convenient since they lump both kinematics and kinetic information.

Although, choosing the parameters in gait analysis widely depends on the

orientation of the gait assessment purposes. And the purpose of gait analysis can

be summarized as to describe the differences between a patient and a nondisabled

subject's performance, to classify the severity of a disability, to determine the

efficacy of intervention, to enhance performance as well as to identify the

mechanisms causing the gait dyshction and to establish design criteria and

quality control methods for prostheses (Seliktar and Bo 1995.. Otais 1995).

2.8. Statistical approaches and gait analysis

Generally speaking, statistical methods are used to classify data for

W e r analysis. Many advance statistical methods are applicable for classifying,

and determining difference and/or relationship between the two or more variables.

In some recent studies, investigaton reduce the quantity of gait parameters

(Wooten 1990.. Olney 1992., Olney et al. 1994.. David and Vaughan 1993) by

mean of applying some advance statistical methods such as Principal Component

Analysis. Multiple Regression Analysis, etc. Among them, several approaches

can be used to reduce and classify the data such as Principal Component Analysis

(PCA), Canonical Correlation Analysis, Cluster Analysis, neural network and

Chapter 2 - Fundamentalof Gait Analysis 54

Fourier Analysis.

However, since all above-mentioned approach= are explanatory

method, thus confirmatory statistical method should be used for further gait

evaluation In the present study, the general objective of this study is to analyze

able-bodied subjects gait focusing on evaluation of the asymmetry assumption

PCA were used to identify most important gait parameters using the temporal,

mechanical muscle power and their associated energies. While t-test for pair data

was used to distinguish significant differences between the selected gait

parameters and their corresponding parameters in the conaiateral limb.

Furthermore, standard Pearson correlation coefficient, and Canonical Correlation

Analysis (CCA), was used to hnd out the relationship and interaction between the

several gait parameters. In the following, those advance statistical methods,

which have been used in this study, are briefly reviewed.

2.8.1. Principal Component Analysis as a reduction and

classification

Researchers o h face with data involving a large number of correlated

variables. These variables may constitute a set of potential predictors, a set of

potential responses, or simply a set of variables needing to be described or

intqreted together (Kleinbaum et al. 1987). In any case, two types of questions

usually arise:

Chapter 2 - Fundmn~~toro/Gait Analysis 55

1. Can a small set of variables be used to replace the entire

original set?

2. What are the underlying dimensions (or characteristics) being

measured by the entire set of data?

The first question concern variable reduction The goal of reduction may

be to e l i d e collinearity. to simplify data analysis, or to obtain a parsimonious

and conceptually meaningful summary of the data The reduced set of variables

may be either a subset of the original set or a newly defined set of variables

derived from the original set. The purpose of Principal Components Analysis is

to explain as much of the total variation in the data as possible with as few factors

(i.e., Principal Components) as possible. In other words, Principal Components

Analysis is a method for data reduction

The Principal Components seek a few underlying dimensions that

account for patterns of variation among the observed variables. Underlying

dimensions imply ways to combine variables, simplifying subsequent analysis.

For example, a few combined variables could replace many original variables.

Advantages of this approach include more parsimonious models, improved

measurement of indirectly observed concepts, new graphical displays, and the

avoidance of multizollinearity.

PCA thus works well with regression, which in some ways they

resemble. Linear relation among pairs of measurement variables, lie at the heart of

all three methods.

In short, steps which are called Methodological Steps in PCA include

selecting and measwing a set of variables, preparing the correlation matxix,

extncting a set of factors iium the correlation ma& determining the number of

components, (probably) rotating the components to increase interpretability and

finally, interpreting the results. Although there are relevant statistical

considerations the most important test of the analysis is its interpretability.

It is often found that the first principal component, PC(I), represents an

overall measure of the information contained in all the variables. Such a general

index usually has a large factor loading (in absolute value).

2.8.2. Differentiation and relationship analysis methods

Several statistic modules will compute measure of significant differences

and correlation to express the relationship between two or more variables.

Differential method were used to find out the probability of existence of

differences between the lower limbs parameters while correctional studies were

applied to define the relationship among gait parameters. Because walking is an

integrated process, differences between the same parameters in the lower S i b can

be explain or a change in one of the parameters will likely have an effect on other

parameters. These are the two main goals of the differential and correctional

studies. This aspect is covered in this study using student t-test for pair data,

standard Pearson correlation coefficient, as well as canonical correlation analysis.

Chapter 2 -Fundamental of Gait Analysis 57

The methods applied in this study will be reviewed briefly in the following.

The t-test for dependent (correlated) samples is the most commonly used

method to evaluate differences in means between two groups. Specifically, if the

two groups of observations that are to be compared are based on the same sample

of subjects. If there are more than two correlated samples and one dependent

variable then analysis of variance (ANOVA), and in case of more than one

interrelated dependent variable and multivariate analysis of variance (MANOVA)

should be applied. The assumptions of the t test for independent samples also

apply to the dependent sample test; that is, the difference scores should be

normally distributed.

The standard Pearson product moment correlation coefficient (r)

measures the extent to which two variables are linearly related. A common first

step of many analyses that involve more than only a few variables is to run a

correlation matrix of all variables and then examine it for expected and

unexpected significant relations.

In case of multiple dependent as well as independent variables,

Canonical Correlation Analysis is appropriate. The canonical correlation module

is an additional procedure for assessing the relationship between two sets of

variables.

Some computational issues involved in canonical correlation analysis

(CCA) are: eigenvalues, the proportion of variance accounted by the correlation

between the respative variant factor structure, canonical correlation as

Chapter 2 - F w r d o m e ~ ~ ~ l of Gait Analysis 58

correlation's patain to the canonical variant, canonical weighf testing the

significant of the canonical mot, canonical score, and finally plotting canonical

scores.

2.9. Summary

Measurements of kinematic variables descriie the subject and his ability

to maintain an erect posture and to control smooth f o r d progression

Simultaneous measurement of the rotations occurring at each segment enable the

examiner to observe individual variables or c o m b i i pattems of motions that are

difficult to assess visually. For a complete kinetic analysis of each body segment,

additional measurements are needed. There are angular displacements, velocity,

and acceleration, anthropornetric data, and external force data such as gravity and

the ground reaction force.

The inverse dynamic approach have been used in gait analysis since

direct measurement of the forces and moments transmitted by human joints, the

tension in muscle groups, and the activation of the pkphaal and central nervous

system is fiaught with methodological problems (Vaughan, 1992).

The body changes its configuration during walking. Thus the forces

acting on each segment and across each joint change with movement Muscle

action is necessary to do the work of raising the body against gravity and

accelerating and deceledng the various segments of the body. Calculations of

Chapter 2 - Fundomenml of Gait Analysis 59

the mechanical energy. work, and power output of each body segnent during the

gait cycle permit an assessment of how efficiently the muscles control the

movement and how well the body uses its metabolic and mechanical energy

resources.

111 - Literature Review

3.1. Introduction

Walking is a basic requirement for normal activity (Pratt 1994) and one of

the most universal of all human activities. The main important task of the lower

extremity is keeping the body upright and carrying it around or during walking.

Those functions are controlled by mechanisms of locomotion and posture of the

nervous system and by the major muscles. Walking is a complex motor skill and

is governed by several her-linked pathways h m the cortex above to the muscle

below (Joffeir 1992). This chapter provides information concerning

investigations, which have been done in able-bodied gait analysis, gait

symmetrylasymmetry and relationship.

3.2. Able-bodied gait analysis

The main task of the lower extremities during gait is to keep the body

upright, to carry or displace it in an orderly and stable manner. The main goal

Chapter 3- Lileranue Review 61

of the gait study is to describe and understand the nature of this easy to do but

complex phenomenon

Many attempts have been made to characterize and standardize able-

bodied gait (data (Allard et al. 1996.. Apkarian et al. 1989., Kadaba et al. 1989..

Eng and Winter 1995., Vauphan et al. 1992). Standardized gait pattern allows

the clinician or gait analyst to compare pathologic gait patterns with a gold

reference. However, the variability of gait data, even among normal subjects is

well known (J-asko-McCarthy et al. 1990., Winter, 1980.. Loslever et al. 1994).

To a cemin degree one's gait pattern is due to one's individual nature (Inman,

1980). There is also evidence that variability in gait increases with age @obbs et

al. 1992.. Winter et al. 1990).

3.3. Gait symmetry/asymmetry

Many gait analyses have focused on the biomechanical aspects of the right

limb, assuming similarity with the contra-lateral S i b while some studies have

addressed asymmetry in gait In the following, gait symmetry will be defined and

discussed in terms of motor control consideration, physics of asymmehy, limb

dominance and gait asymmetry indices.

Chapter 3- Litsahlre Review 62

33.1. Definitions of symmetry

Symmetry has been defined as the similar anangement in form and

relationship of parts around a common axis or, on each side of a plane of body

(Domalds 1994). Pafect agreement between external kinematics of the left and

right limbs was also used to define symmetry (Herzog et al. 1989., Soudan et al.

1982). Meanwhile, asymmetry was defined as a statistically significant difference

between limbs for each variable measured (Gunderson et al. 1989).

33.2. Motor Control

There is enough evidence that showed the gait analysis should take into

consideration the role of motor control sciences and its branches to better

understand the gait phenomenon Here, a few aspects of involvement of this area

with symmetry assumption will be reviewed.

It is accepted that the two hemispheres of the brain are different in motor

organization and function$ (Cam& et al. 1983, Colbome et al. 1992.. 1994).

The left hemisphere is more specialized for the precise tempoml control of fine

motor actions of the left and right sides and language processing, (cbagha and

Tesiol 1983.. Colbome et al. 1994) while the righ: hemisphere is related to the

bilated somatosensory spatial ability, emotional expression, and motor functions

(Dickey and Wmter 1992).

Chapter 3- Liternave Review 63

In about 95 percent of all persons, the left hemisphere is dominant and in

the remaining 5 percent either both sides develop simultaneously or more rarely,

the right side alone becomes highly developed. In more than one half of newborn

babies, the area of the wrtex that will eventually bewme Wemike's area at the left

hemisphere is larger than the right (Guyton 1991., Waziri 1980). However, if for

some reason the left side area is damaged or removed in early childhood, the

opposite side of the brain can develop full dominant cbacteristics.

The proximal and axial neuro-motor mechanisms must be involved to

explain functional tasks of lower extremities. Asymmetry was reported in

counting the number of motor neurons at the third sacral vertebra level of five

persons (Irving et al. 1974). Irving et al. (1974) have documented that the

numbers of motor neurons on one side of some subjects were twice those of the

other side. In gait studies, asymmetries are also demonstrated by differences in

the neuromuscular drive in the muscles involved in a given movement as

measured by EMG (Ounpuu and Wmter 1989.. Boucher and Hodgdon 1991.,

Eke-Osoro 1994).

Lateral dominance, as the preferential use in voluntary motor acts can be

determined h m arm, ear, eye and leg functions @ o d d s 1994). Horton (1969)

studied the laterality to determine the effect of learning in both sida of the body

(Horton 1969). while Duchatinicr and Rozendal (1970) evaluated the type of

cognition Furthermore, l a t d t y has been also studied to determine the

relationship of the hand, foot, eye and ear preferences to each other (Devita et al.

1991, Eldestien 1991, Ensberg et aL 1990,1991.. Boucherand Hodgdon 1991).

In gait analysis laterality has been evaluated as a secondary objective to explain

gait symmetry (Hamill et al. 1984, Hannah 1984, Ounpuu and Wmter 1989,

Gunderson et al. 1989).

333. Physics of asymmetry

Hae, gair symmetry and laterality (limb dominance) will be reviewed in

terms of anatomical and mechanical aspects of human movement. The

mechanical asymmetries are often due to differences in bone to bone interactions

as well as leg length inequality (LLI)) as reported by Delacerada and Wykoff

1982.. and Subotnik 1981b. Side differences in cross-sectional geometric

properties indicate that the left lower limb bones are generally larger (Pomeranb

and Harris 1980., Petm 1988 ) and heavier (Chibber and Singh 1972, Pctm

1989) than those of the right lower limb in right handed persons.

Asymmetries in muscle activity, (Taillard and Monchher 1965, Fribrcg

1978). low back pain and scoliosis (Wiltes 1971.. Subotnik 1976., 1981a, 19Slb..

Giles and Taylor 1981., Fribreg 1983), decrease in strength on the short leg side,

(Bolz and Davis 1984), negative effect on oxygen usage, (Delacerada and

McCorory 1981), and reduction in the biomechanical efficiency of ambulating

(Dillman 1975) also have been addressed.

Chapter 3- Limmue Revim 65

Different outcomes in gait symmetry are most likely due to the definition

used (Hazog et al 1989.. Soudan 1982). the gait laboratory set-up and protocol

limitations (Harris 1955.1958, Horton 1969, Herzog et at 1991, Hinrich 1992).

symmetry assumption for simplicity (Hamill et a]. 1984), pooling the data across

subjects (Murray et al. 1967.. Ounpuu et aL 1991), differences between clinical

and statistical approaches (Gunderson et at 1989) and selection of gait parameters

(Hamill et al. 1984., Baur et al. 1993).

33.4. Gait analysis and symmetry

Most gait analyses focused on the biomechanical aspects of the right limb,

assuming similarity with the contra-lateral limb. Symmeby has been reported in

terms of foot-floor contact and photographic recording of the hips, the knees, in

three successive walking cycles, (Vanden der Shaaten 1978). Claeys 1983

addressed symmetry in the vextical and horizontal reaction forces of 214 normal

subjects. Using bilateral bsdimensional electmgoniometers in twelve able-

bodied subjects, Hannah et al. (1984) have shown joint motion symmetry between

the hips in all three planes and at the knees in the sagittal plane during natural

walking. Hamill a al. (1984) found no significant difference between the limbs in

11 vertical, 5 anterior-posterior and 4 medio-lateral charcicteristics of the ground

reaction fones in walking and running. These results were later confirmed by

Menard et aL (1992), in a study where eight normal subjects walked at their natural

Chap~er 3- Lireranue Review 66

speed. Furthermore, symmetry in strength of plantar-flexion and dorsi-flexion of

nineteen normal subjects was reported by Saw et al. 1993.

However, there are a number of bilataal investigations where gait

asymmetry was documented Sin$ (1970) claimed that the lower limbs are not

used equally during walking. Rosenrot a al. (1980) reported that the duration of

the initial and terminal double support periods were not identical, as would be

expected in young healthy subjects. Asymmetry in peak vertical anterior-

posterior, media-lateral components of the ground reaction force of 62 able-

bodied subjects were documented ( H a g et al. 1988). According to Crowe et al.

(1993, 1995). consistent gait asymmetry could be defined in terms of oscillation

of the body center of mass. Dickey and Winter 1992 reported asymmetry at the

hip in able-bodied subjects.

Additionally, asymmetry was documented in planter flexion strength and

calf circumference (Damholt and Tamansen 1978). in sagittal and frontal planes

forces and moment (Balalaishman and Trump 1982). in velocity profiles, (Law

1987). step length, (Barr et al. 1987.. Barker and Hewison 1990) stride width,

(Chodera 1974, 1973). foot placement angle (Chodera 1973), maximum knee

flexion during stance maximum knee flexion during swing (Barr et al. 1987),

double support time in childhood (Rose et al. 1991). and range of joint motion,

(Stefangsyn and Ensberg 1994).

The aim of locomotion is to support the body against mass while

generating movements to propel the body f o d It requires precise

Chapter 3- Lireranue Review 67

coordination between the tasks of propulsion, and balance (Winter, 1990). In

recent gait studies, asymmetry has been explained by a functional behavior of

lower extremities. Hirasawa (1981) claimed that the left and right lower limbs

have a supporting and a moving function, respectively. In evaluating maximum

amplitudes of the lateral component of the ground reaction force of twentyeight

subjects Matsuska et al. (1985) found that the medial-lateral balance in walking

was mostly controlled by the lefl l i b .

For 53 males and 39 females walking at slow, kee and fast walking

speeds, Hirokawa (1989) associated propulsion with the right l i b while the lefl

l i b was found to be responsible for suppon Allard et al. (1996) were among the

first to report simultaneous bilateral thrre-dimensional inverse dynamic gait data

in 19 able men. Asymrnehies in the peak muscle powers as well as in their

corresponding energies were found. Though both limbs generated the same tolal

energy, the higher total energy absorption in the right l i b was attributed to its

control.

33.5. limb dominance

No statistically significant difference has been found between the

dominant and nondominant limbs of twelve able-bodied subjects using an

electrogoniometer (Hannah et al. 1984). Similar results were reported by Hamill

et al. (1984) using temporal and kinematic parameters. In another study, Barkers

Chapter 3- Literanire Reriew 68

and Hewison (1990) reported no statistically significant differences between right

and left lower limb scores (as limb symmetry indcx) or dominant side.

Though Gunderson et al. (1989) concluded that asymmetry cannot be

related to lateral dominance, Rosenrot (1980)., Wheelright et al. (1993). claimed

that gait asymmetry was related to laterality. Furthermore, several investigations

have suggested that asymmetry is relevant to laterality. Singh (1970) and

Rosenrot (1980) claimed that one lower l i b appears as the dominant limb.

Moreover, Damholt and Termansen (1978) reported that 60% of their subjects

were stronger on their dominant limb. This study was confirmed later by Giles

and Taylor (1981) which reported that the dominant leg was on the average

15.8% stronger than the nondominant leg in plantar flexion seength.

According to Matsuska et al. (1985) medial-lateral balance in walking was

conmlled by the nondominant hemisphere. Devita et al. 1991 also confirmed

the effect of lateral dominance in gait They found that the right limb of their

subjects generated 56.1% to 61.0% of total positive work during n a w ! speed

walking.

Arsenault et al. (1986) also found amplitude asymmetries in EMG profiles

of the Soleus and Rectus femoris muscles, while later on Boucher and Hodgdon

(1991) documented asymmetry at the Right Vastus medialis oblique versus right

Vastus lateralis during leg extension O q u u and Winter (1989) found some

evidence to suggest that the plantar-flexor elatromyography (EMG) activity be

related to l i b dominance.

33.6. Gait symmetry indices

To determine gait asymmetry, different methods have been used, namely

statistical and symmetry indices and self-report. Gunderson et al. (1989) have

used a two-way multivariate analysis of variance (MANOVA) with repeated

measure because the temporal and kinematic variables were not independent of

one another. A Newman-Keul post hoc test was performed for w k b h h w h g

a significant within-subject difference between limbs. They also used a Pearson

product-moment correlation to determine the relationships among the 12

measured gait variables. Hannah et al. (1984) passed a best-fit d g h t line

between the right and left data sets. Perfect symmetry was expressed by a

coefficient of value one. They observed that in the frequency domain, the

detection rate of asymmetries is markedly improved.

The symmetry index (SI) proposed by Robinson et al. (1987) was used by

H a g et al. (1989) to determine asymmetries in ground reaction force patterns in

normal gait Using this index Becker et al. (1995) were able to show that the

successful surgical trea!ment of ankle fiacm in young adults resulted in an

improvement of gait symmetry in terms of plantar pressure distribution

The ratio of the value of one limb over the other was used by Gnapli et

al. (1974) to investigate peak velocity during the gait cycle of bel-#-knee

amputees and by Andres and Stimrnel(1990) in assessing lower l i b prosthetic

Chap fer 3- Liferamre Review 70

alignment Wall and Turbull(1986) to determine temporal gait asymmetries also

applied it in 25 patients with residual hemiplegia.

L a t d t y in tams of questioners or self-repon (Dean 1982, Liederman

and Healey 1986) and observation or practical (Dorill and Thoreson 1993., Peters

1986) also have been used in a few studies In the present study, laterality was

determined 6um five activities, involving: I) kicking a ball, 2) throwing a ball, 3)

writing, 4) opening a jar. and 5) hopping on a single l i b .

3.4. Purpose of th is study

To some, able-bodied gait is the mean pattern of a large control group of

subjects with which everyone else's gait pattern a be compared. To others.

able-bodied gait is that of a single subject rather than that of control group. Bates

et al. (1992) considered the subject to be a random response generator making

each hid independent 6um another. Though many are using their own control

data, little is known about the homogeneity between the groups of able-bodied

subjects.

The first objective of this study was to present the basic three dimensional

muscle power pattem as well as extreme cases of normality which we must be

a w m of in our interpretation of normal gait

The second objective were a) to identify the temporal, peak mechanical

muscle powers and mechanical energies parameters developed by the lower l i b

Uurprer 3- Liferamre Review 71

during natural speed walking to determine those parametas related to gait

propulsion and contolling in locomotion and b) to explain functional gait

asymmelry based on propulsion and control in order to identify temporal, peak

mechanical muscle power and their associated mechanical energies.

The third objective was to explain gait relationship in terms of identified

peak mechanical muscle power and their associated mechanical enagies

developed by the lower limb during natural walking speed in each lower l i b in

terms of propulsion and control tasks.

Chapter 4

Papers

The main thrust of this study has been published or submitted for

publication in one book chapter and as two papers. The first paper provides

information on the desniption of men and women able-bodied gait The

second and third papers detail functional asymmetry and its relationship to

gait in t m s of forward progression and control tasks of lower extremities

using three-dimensional, simultaneous and bilateral tempo;al, kinematic and

kinetic parameters.

Paper 1:

Men and women able-bodied gait

This paper has been published as a book chapter in a book entitled Three dimensional analysis of human locomotion

edited by Allard, P; Cappozzo, A; Lundberg, A, Vaughan C. The book published by John Wiey & Sons. Chapter 15, p :

307-334.

Men and women able-bodied gait

Paul Allard", R&is Lachance",Rachid Aissaoui", Heydar Sadeghi" and

Moms Duhaime").

'Department of Physical Educah'oq Univexsity of Montreal, Montreal. PQ,

CANADA

'Research Center, Sainte-Justine Hospital, 3175 CBte Ste-Catherine, Montreal,

PQ, H3T 1C5, CANADA

'Shriner's Hospital, Montreal, PQ, CANADA

All correspondence should be addressed to Paul All@ Ph.D, P.Eng. Rescarth Center Sainte-Justine Hospital 3 175 CBte Ste-Catherine Montreal, PQ, H3T 1C5 Canada Tel: (5 14) 345-4740 Fax: (514) 3 4 5 4 0 1 E-mail alIardp@ere.urnontreal.ca

Chaprer 4- (Paper I): Women and men able-bodiedgait 73

1. Introduction.

To some, able-bodied gait is the mean pattem of a large control p u p of subjects

having no major orthopedic or neurological disordas, which may affect their

locomotion It is often associated with the normal gait pattem and is therefore the

gold standard with which everyone else's gait pattern is compared. To others,

able-bodied gait is that of a single subject rather than that of a control group.

Such an able-bodied subject may exhibit large variations from the mean control

p u p data, making comparison either difficult or misleading. Bates et al. (1992)

consider the subject to be a random response generator making each trial

independent h m one another. Though many are using their own control dala

little is known about the homogeneity befween the p u p s of able-bodied subjects.

Able-bodied gait is presented here to highlight the basic paftem as well as some

extreme cases of normality of which we must be aware when interpreting normal

gait

Able-bodied gait has been well described in the literature. The pioneering work

of Braune and Fisher (1987a,b) originally published in late 1890 and early 1900

was the fim to deal with the three-dimensional aspect of human ambulating by

means of two-sided chronophotography. Their work was applied to the study of

the German infantry soldier. Much later, Klopsteg (1954) and Inman et al. (1981)

in the Biomechanics Laboratory at the University of California in San Francisco

Chapter 4- (Paper I): W o r n andmen able-hiiedgnir 74

and Berkeley reported fundamental three-dimensional data on normal and

amputee locomotion for the design of artificial limbs. Since then. three-

dimensional gait analysis mahods and so- have been published to meet the

needs of the students of human motion (Vaughan et al., 1992). Vaughan and his

colleagues bring togerher the theory of 3-D invase dynamics applied to human

gait and the tools required performing its analysis. Nard a al. (1994) reviewed

the current practices in data capture, three-dimensional reconstruction techniques

and modeling techniques in human movement as well as upcoming trends. But,

comprehensive normative 3-D gait data are reported for the first time in Crak and

Oatis (1995) by a number of contributors. Aside fiom the temporal and p h i c

panmeters, nonnative gait data were obtained h m a single S ib .

Normative data are provided here from a group of 10 male and 15 female able-

bodied subjects. Their anthropometric characteristics are given in Table 1. None

had presented any orthopaedic or neurological disorders, which could affect their

waking patterns. They were generally students in the Depzbnent of Physical

Education a! the University of Montreal but none were national or provincial level

athletes.

Data for the right limb of male subjects are first presented since it was the

dominant side. Contralateral limb data are presented in the following section on

Chauter 4- P a w I): Women andmar able-bxiiednait 75

symmetry and finally, data of able-bodied women are discussed before

concluding.

Table 1: Anthropomeeric data for the male and female able-bodied groups

Male Female

Number of subjects 10 15

Numberoftxials 30 45

Age (Years) 2531 (o 4.82) 20.13 (o 220)

Height (m) 1.79 (o 0.06) 1.67 (o 0.04)

weight fig) 76.95 (a 1129) 62.03 (o 5.61)

2. Men able-bodied gait

There are only a few three-dimensional studies and fewer simultaneous bilateral

evaluations of able-bodied gait After the presentation of the spatio-temporal

parameters, the results will be firstly discussed with respect to those obtained

h m the right limb of able-bodied men since they are the most commonly

available data. Then, bilateral data will be briefly presented and gait symmetry

will be discussed

2.1 Spatio-temporal factors.

The mean values of the spatio-temporal factors are given in Table 2. These data

fall withi? the range reported by Craik (1995) where walking speeds is between

1 2 and 1.5 m/s with a cadence varying between 100 and 120 steps p a minute.

Chapter 4- (Paper I): Womcn and mcn able-bodidgait 76

isberg a al. (1993) have performed similar an analysis for a group of 233 healthy

subjects whose age varied between 10 a d 79 years. For similar age groups, the

walking speed was similar to our data but their cadence was slightly higher at 120

stepslmin. The difference may be explained in part by the methodology used to

determine the spatio-temporal parameters. isberg et al. (1993) used two

photocells at a 5.5m interval and average values were taken fium 13 waking

trials. Our data are derived fium a video-based system operating at 90Hz

Table 2 Phasic parameters for an able-bodied men group and two subjects of

that group.

Able-bodied group (N=30)

Right limb Left l i b Mean o Mean o

Stance gait speed (mk) 1 3 1 0.1 1 1.33 0.09

Cadence (steplmin) 106.9 7 2 108.8 6.7

Stride length (m) 1.467 0.061 1.458 0.056

Step length (m) 0.735 0.044 0.720 0.033

Stance phase (%) 60.98 1.74 61.16 1.23

Swing phase (%) 39.02 1.74 38.84 1.23

Initial double support (%) 10.52 1.83 10.64 1.87

Terminal double support ("h) 11.44 2.05 1 1.56 2.02

Total double support (%) 21.96 2220

Individual data

Subject1 Subject 2 1.30 1.34

103.8 105.8.

1.432 1.469

0.820 0.729

58.59 59.79

41.41 40.21

9.09 12.37

12.12 11.34

21.21 23.71

Individual able-bodied gait does not necessarily follow the average pattern

d m i by the goup. The spatio-temporal faaors of two male subjects, which

Chapter 4- (Paper I): W o r n and men able-bodiedgaiz 77

have essentially the same natural wallcing speed as our able-bodied group, are also

presented in Table 2 This was achieved by modulating their stride length and

cadence accordingly. Their stance and swing phase relative duration are typical.

Yet, the initial and taminal double support periods are higher though within the

limit delineated by the standard deviation of the able-bodied group.

Generally, the data of the two subjects fall within one standard deviation of the

able-bodied group. On the average, the standard deviation represents 9% of the

mean value with the smallest being the stance or swing phase relative duration

(4%) and the highest the double support periods (18%). Does this reflect the

presence of more than one able-bodied gait panern?

212 Kinematics.

Kinematic data such as l i b segment displacements, speeds and accelerations or

joint range of motion are essential for estimation of dynamic joint reaction forces

and muscle moments and are mostly useful in comparing able-bodied locomotion

with pathological gait Though the literature proliferates with bi-dimensional

data, 3-D normative data are less common Though most studies have focused on

the 3-D kinematics of a single joint, only a few (Apkarian et al., 1989; Patriarco et

al., 1981, Kadaba et al., 1990) have reported hip, knee and ankle ranges of motion

during normal locomotion

Chnpter 4- (Paper I): Women andmen abIe-bodiedgai~ 78

Wu (1995) altmds our attention to the estimation of linear acceleration obtained

by direct measurement or derived from displacement data Though the overall

pattems are in good agrament throughout the gait cycle, she reports a lack of

impact acceleration at heel-strike when using a differentiation method The

smoothing or the filming techniques themselves influence the results and u n

render comparison difficult between different kinematic data sets (AUard, et al,

1990).

Wu (1995) also reports that 18 parameters ye required to describe the kinemdcs

of a single limb segment - linear and angular displacements, velocities and

accelerations. If one considers the lower and upper limbs as well ar the bunk

(upper and lower sections) and the head, a 15-link segment model would yield

270 parameters. The kinematics of the center of mass of the whole body (9

parameters) and the joint ranges of motion description (72 parameters) must be

added! The reader is referred to the above publications for fuIther information as

well as for normative data. Among these, Kadaba et al. (1990) present average

data of nine gait cycle from each of the 40 subjects (N=360).

2.13 Mornen* muscle powers and mechanical energies

Although ground reaction forces and muscle moments are usell parameters to

describe human locomotion (Henog et al., 1989) and to quantify gait disorders,

Chapter 4- (Paper I): Women and men able-bodiedgait

muscle powers provide a good indicvion of the pason's ability to control and

propel the lower limb. Muscle power has been defined by Wmter (1990) as the

rate of work done muscle. It is expressed as the product of the net muscle

moment and angular velocity and can be either positive or negative. When the

sign or the polarity of the moment and the angular velocity are the same their

product is positive. This represents a power generation and is associated with a

concentric muscle contraction When the polarities are of opposite s i g y the

power is negative and this corresponds to an acentric muscle contraction

Muscle powers and their corresponding moments are given in Fig. 1 to 3. The

muscle power bursts have been labeled according to Eng and Winter (1995).

These were obtained h m 10 able-bodied men and represent 30 simultaneous

bilateral trials. Right limb data was normalized with respect to body weight and

expressed in percentage of the duration of the gait cycle (GC). Thc standard

deviation calculated at each percentage of the GC is overlaid on the right limb

mean data. Data of the left limb are also shown on the same figure. The left limb

b r '5e swing phase at about 10% of the GC of the right limb and toe-off

occurred at about 112% of GC. This representation of bilataal data has the

advantage of keeping the temporal relationship between the limbs, which

unportant for taking into account asymmetries in pathological gaits

Chrpfer 4- (Papm I): IVomar and nun able-bodied gait 80

A word of caution must be addressed before examinkg the power curves The

sagittal moments are generally comparable; however, the moments calculated in

the hntal and transverse planes vary widely 6um one study to another. For

example, Crowininshield et al. (1978). Bowsher and Vaughan (1995) and

Kadaba et al. (1989) reported an internal hip rotation moment between 5% and

25%GC followed by an external moment afterwards while Apkarian et al.

(1989) and Eng and Winter (1995) founF the opposite. At the ankle, Apkarian

et al. (1989) documented an inversion moment while Kadaba et al. (1989)

reported an eversion moment In the Eng and Winter (1995) study, the subjects

developed an everted moment at the ankle, which was followed, by an inverted

moment We assume that this variability in the results are due to either different

normal walking patterns, adaptations to control the lower limb or a combination

of both.

Fig. 1 Joint a) moments and b) muscle powm developed at the ankle in ten able-

bodied men.

Gapm 4- (Poper I): Women mad men able-bdaigair 81

Fig. 2 Joint a) moments and b) muscle powers developed at the knee in ten able-

bodied men

Fig. 3 Joint a) moments and b) muscle powers developed at the hip in ten able-

bodid men.

Recently, three-dimensional muscle power data have been used to describe both

normal (AUard et al. 1996; Ounpuu et 4 1991 and Eng and Winter, 1995) and

pathological gait (Allard et al., 1995. Czerniccki et al, 1991 and L o i et al.,

1995). The reader is x t f d to these publications for a detailed explanation of

the powm absorbed and generated during gait and should keep in mind that

r o w m and energies are scalar terms and they were partitioned into three

arbitrary planes to facilitate data interpretation

The mechanical energy obtained by time integration of the power curves, are

reported in Table 3 to 8 for the 30 trials as well as for two individuals who were

a part of the able-bodied group.

The individual data followed the energy absorption and genetation panem of

the able-bodied group with the exception of K4 burst Subject 1 had stronger

energy absorption than of the control group while subject 2 generated 14.07

JkglO-'. Large variation was also noted between the two individuals. For

example, the H2 energy absorption was 14 times higher in subject 2 but the H3

generation was nearly five times higher in subject 1. This brings out that

individuals may not comply completely with a group mean but may have

different but still quite normal patterns.

Table 3: Energies in Jkg 10' developed by the right m the sagittal plane for men.

Able-bodied group Individual data Joint Burst Mean Standard Subject 1 Subject2

Deviation

Ankle AIS A2S

Knee KIS K2S K3S K4S

Hip HIS H2S H3S

Table 4: Energies in Jikg 10' developed by the right limb in the fiontal plane for men. Able-bodied group Individual data

Joint Burst Mean Standard Subject 1 Subject2 Deviation

Ankle AIF -2.10 1.84 nil -0.90 A2F 1.60 0.94 2.00 nil

Knee KIF 0.50 1.01 0.77 0.82 K2F -1.90 2.89 -1.61 -2.75

Hip HIF -16.40 8.25 -1 1.80 -21.47 H2F 1.10 1.40 137 1 S O H3F -1.40 1.18 0.000 -237

Table 5: Energies in Jikg 10' developed by the right limb in the transverse plane for men. Able-bodied group Individual data

Joint Burst Mean Standard Subject 1 Subject2 Deviation

Knee KIT 120 0.76 1.67 0.53 K2T -0.90 0.68 -1.83 -1.03 K3T 030 034 0.00 1 A7

Hip HIT -1.60 157 -1.60 -2.10 H2T 4.10 2.12 1.07 0.90 H3T -1.00 1.09 -1.00 -1.57

Chaprer 4- (Paper I): Women and men able-bodldgai! 84

Table 6: Energies in Jkg 1@ developed by the men able-bodied group in the sagittal plane by both limbs.

Ablcaodicd group (N=30) Right limb Left limb

Joint Bu% Mean Standard Mean Standard Deviation Deviation

Ankle A1 -1830' A2 27.60

Knee K1 -5.00 K2 5.00 K3 -13.60' K4 -15.00*

Hip HI 10.00' H2 -14.10' H3 21.70'

Total limb genaated 64.70 21.15 70.90 19.94 Total S i b absorbed -66.00' 14.84 -37.90. 952

Table 7: Energies in Jkg 10" developed hy the men able-bodied group in the frontal plane by both limbs.

Able-t'uodied group (N=30) Right limb Let? limb

Joint Burst Mean Standard Mean Standard Deviation Deviation

Ankle XlF A2F K1F K2F

Hip H1F H2F H3F

Total limb generated Total limb absorbed

Table 8: Energies in Jkg 1 p deveiopbd by the men able-bodied group in the trar~ase plane by both limbs.

Able-bodied pq (E:=30) Right limb Lefi limb

Joint Burst Mean Standard Mean Standard Deviation Lkviation

Knee KIT 120 0.76 0.90 0.94 K2T -0.90. 0.68 -0.60* 057 K3T 030 0.34 0.20 0.44

Hip HIT -1.60* 157 -0.90* 137 HZT 4.10 212 3.90 270 H3T -1.00 1.09 -0.60 0.69

Total limb generated 5.60 2.06 5.00 338 Total limb abs~rbed -350* 1.60 -210, 1.83

3. Gait symmetry.

The main task of the lower exlmnities during gait is to keep the body uprigh~ and

to displace it in an orderly and stable manner. Since the gait patterns of the right

and left lower limbs were assumed to be symmetrical, numerous able-bodied gait

studies have relied on unilateral data (Apkarian et al., 1989; Kadaba et al., 1989;

Eng and Winter, 1995; Sutherland. 1984; Vaughan a al.. 1992). There has been a

number of bilateral gait studies but often limited to the assessment of a single

limb at a time (Loizeau et aL, 1995). Ounpuu et al. (1991) obtained 3-D bilateral

simultaneous data on 31 c h i l h but reported combined right and left l i b

values. Using bilateral tri-axial electrogoniomaen attached to the hips and the

knees. Hannah et al. (1984) concluded that their 12 able-bodied subjects walked

with reasonable symmetry. Recently, Allard a al. (1996) presented temporal and

3-D bilateral kinematic data obtained h m 19 ablcbodied male subjects. They

reported statisfically different mcdmnical energies for the right and left limbs

even though both limbs had the same walking s p e d

Anthmpometxic factors, dominance and orthopaedic disorders may interfere with

gait symmetry. Chhiiber and S i (1970) have found that the muscle weight of

the right l i b was significantly greater on the dominant side. though no

correlation has been found between the upper and lower limb dominance. M e r

assessing lower limb dominance by means of the mobility and stability tasks.

Gundersen et al. (1989) performed a bilateral planar kinematic analysis of 14

able-bodied subjects. They concluded that symmetry can not be assumed but

should be examined in relation to the subject's own variability and could be

predicted by the dominance.

The lit- is divided in support of gait symmetry. There are numerous studies

which document gait symmetry in terms of temporal parameters (Hamil et al.,

1984 ; Vanden der Stmaten and Scholton, 1978), kinematics (Hannah et al., 1984,

Rosenrot, 1980) and ground reaction forces (Harnil et al., 1984). Othm reported

gait asymmetry in spatio-temporal parameters (Brandstater et al., 1983).

kinematics (Hinrich, 1992), kinetics (Hemg et al., 1989) and electromyographic

activity (Arsenault et al, 1986; Olmpuu and W w , 1989). n e presena of gait

asymmetry is definitely confirmed though some subjects may &'bit less than

othas. Some questions still remain to be answaed: which gait parametas are the

most sipifica* why is asymmetry present and what causes.

To determine gait asymmetry, different methods have been use$, namely

statistical and symmetry indices. Gunderson a aL (1989) have used a two-way

multivariate analysis of variance (MANOVA) with repeated measures because the

temporal and kinematic variables were not independent of one another. A

Newman-Keul post hoc test was performed for variables showing a significant

within-subject difference between limbs They also used a Pearson product-

moment correlation to determine the relationships among the 12 measured gait

variables. Hannah et aL (1984) passed a best-fit straight line between the right

and left data sets Perfect symmetry was expressed by a coefficient of value one.

They observed that in the iirquency domain, the detection rate of asymmetries is

markedly improved.

The symmetry index (SI) proposed by R o b i i n et al. (1987) was used by Herzog

et al(1989) to determine asymmetries in ground reaction force patterns in normal

gait It is expressed as

Chaula 4- If- I): Women and mar oblcbodiadnait 88

where X, and X, w a t the values of the gait variable measured for the right and

left limb respectively. A zero SI index indicates perfect symmetry. Because the

difference between the right and left limb values are reported a s k t their avmge

value, this index has two limitations. Where a large asymmetry is present, the

average value does not c o d y reflect the performance of either limb.

Furthennore, parameters having large values but relatively small interlimb

differences will tend to lower the index and reflect symmetry. Using this index

Becker et aL (1995) were able to show that the successful surgical treatment of

ankle h tu res in young adults resulted in an improvement of gait symmetry in

terms of plantar pressure distriiution

The ratio of the value for one limb over the other was used by Ganguli et al.

(1974) to investigate peak velocity during the gait cycle of below-knee amputees

and by Andres and Stimrnel(1990) in assessing lower l i b prosthetic alignment.

It was also applied by Wall and Turnbull (1986) to determine temporal gait

asymmehies in 25 patients with residual h~niplegia A ratio of one was

indicative of a reciprocal gait pattern while higher or lower values reflected

asymmetries. A similar approach invohing the ratio of the standard deviations

was considered by Klajic et al. (1975) to represent the perfection of the gait

pattern Vagenas and Hoshizaki (1992) developed a new d o

Chnprer 4- (Paper I): Womrn and mrn dle-bodicdgait 89

where R and L stand for right and left limb values rapactively. The swres were

recorted to reflect bichotomized values of 1.0 and -1. Asymmetries larga than

1% wa-e given a value of +I- 1 and in all other cases, 0 to represent symmetry.

Though these indices h v e not been used here to determine the presence of gait

asymmetry, a paired t-test was applied between right and left limb data. The

spatio-temporal parameters did not reveal any significant differences between the

limbs However, differences were noted between the mechanical energies. Most

of the differences were observed in the sagittal plane and were generally

associated wid; energy absorption This was related to the control of the right

limb while both limbs maintained the same speed of locomotion (Allard et al.,

1996).

4. Women abled gait

There has been relatively few studies of able-bodied women gait (Murray et al.,

1970; F i e y et al., 1969). These were limited to the description of the spatio-

temporal and kinematic parameters.

4.1 Spatietemporal factors.

Table 9 presents the spatio temporal parameters obtained firom a group of 15 able-

bodied women. Their average speed and cadence arr respectively about 10%

UIopra 4 (Puper I): W o r n and men able-bodiedgaif 90

faster and 95% slower than a comparable age group in Oberg et al. (1993) but

still well within their 95% confidence limit No significant difference was noted

between the right and left limbs values. The women had a faster walking speed

than the men able-bodied group which can be explained in part by a higher

cadence ( Y d , et al, 1991).

Table 9 Phasic parameters for an able-bodied women group.

Stance gait speed (mls) Cadence (stephin) Stride length (m) Step length (m) Stance phase (%) Swing phase (%) Initial double support (%) Terminal double support (%) Total double support (%)

Able-bodied group (N45) Right limb Left S i b

Mean o Mean o 1.37 1.10 1.37 0.12 1135 6.6 112.8 7.7 1.438 0.058 1.445 0.058 0.725 0.037 0.719 0.032 5930 2.04 59.15 2.06 40.70 2.04 40.85 2.06 9.52 2.08 9.54 2.08 921 2.13 9.54 2.18 18.73 18.78

4 2 Muscle power and mechanical energy.

The muscle powm and the joint moments for the ankles, hips and knees are

presented in Figures 4 to 6. The moments calculated at each joint were similar to

those reported for the men able-bodied group of our study. Fu~thermore, the right

and left S i b moments were generally quite symmetrical. Additionally, the

powers developed at each joint and in each plane were also symmetrical and

similar to those of the men able-bodied group.

Chnpler 4- (Paper I): Women a n d m able-bAiuigair 91

-2 0 , , I . : , , , , , , , , , ,, ,;; & "0 X *I .O U .. 7. .D .O 7.0 I-. 2 i l

. W - m U . U E - . . * L . U ( U . O . C - .

Fig. 4 Joint a) moments and b) muscle powm developed at the m e in fiAeen

able-bodied women

-38 ' . , .- I I , , . , , , , ,

70 ID 39 rJ & m k & ,iO >Ao ' 5 20 W 4.2 I 0 CD 70 m w s0m 19s 120

w-muracn-s + d u w a c n c n n r

Fig. 5 Joint a) moments and b) muscle powm developed at the knee in fifteen

able-bodied women.

Chupter 4- (Paper I): Women and men able-boaYedgait 92

Fig. 6 Joint a) moments and b) muscle powers developed at the hip in fifteen

able-bodied women.

Mechanical energies absorbed and generated are rrpcirted in Tables 10 to 12 for

the sagittal, the hn ta l and transverse planes respectively. Once normalized with

respect to body mass, these values are close to but usually smaller than those

reported here for the ablebodied men. A& the right limb absorbed mom than

the left limb even though both limbs have the same walking speed and similar

energy generation values. The sagittal plane accounted for most of the significant

difflerences and our of the four parameters which were different in both the

women and men groups, three were related to energy absorption

Uurpter 4- (Paper I): Women andmm abIc-bodicdgai! 93

Table 10: Energies in Jkg 10" developed by the women ~de-bodied p u p in the

sagittal plane by both limbs.

Able-bodied group (N=15) Right limb Left limb

Joint Bunt Mean Standard Mean Standard Deviation Deviation

Ankle AIS A2s

Knee KIS K2S K3S K4S

Hip HIS H2S H3S

Total limb generated 58.00 16.82 71.40 19.61 Total limb absorbed -66.80' 2228 -37.90' 12.53

p < 0.05

Table 1 I: Energies in Jkg 10' developed by the women able-bodied p u p in the

frontal plane by both Sibs.

Able-bodied p u p (N=45) Right S i b Left Sinb

Joint Burst Mean Standard Mean Standard Deviation Deviation

Ankle AIF -0.90 0.60 -2.10 1.80 A2F 220 3.46 1.70 1.37

Knee KIF -0.90 0.73 -1.30 1.92 K2F -1.50. 0.81 0.80. 0.66

Hip HlF -13.30f 6.86 -16.90* 8.83 H2F 0.90 1.07 1.10 1.81 H3F -1.50 1.92 -1.30 1.60

Total limb generated 4.60 335 3.60 2.41 Total limb absorbed -16.00 7.54 -2i.60 10.18

Chnp~er 4- (Paper I): Women andmen able-bodiedgaiz 94

Table 12: Energies in Jkg 10.' developed by the women able-bodied p u p in the

bansverse plane by both limbs

Able-bodied group (N=35) Right limb Left limb

Joint Burst Mean Standard Mean Standard Deviation Deviation

Ankle AIT Knee KIT

K2T K3T

Hip HIT H2T H3T

Total limb generated Total limb absorbed

* p < 0.05

4. Trends

Data h m the literature as well as those presented in this chapter show a large

variability in the results obtained for able-bodied p u p s . Even within a p u p ,

gait data of some able-bodied subjects varied h m the p u p ' s mean. This issue

of data variability is further complicated when considering irnultaneous bilateral

information.

Differences between the right and left limbs may reflect a natural S i b adjustment

pattern to maintain a relatively constant walking speed rather than gait

asymmetry. But, normal gait asymmetry may also be present, at least to some

Chapter d- (Papm I): Women andmen abIpbodiedgait 95

extent Different methods have been proposed to quantify gait differences

associated with arymmetry but consensus !ns yet to achieve.

Diffaent methods and approaches have been used to characterize normal and

pathological gait by one or several typical patterns of relevant gait parameters.

Olney et al. (1994) have used multiplelinear &on to determine the

relationship of temporal, kinematic and kinetic variables to walking speed in-

patients with hemiplegia A aep-wise regression identified the moa useful

parameters in predicting speed. Using a principal component analysis approach,

Mah et al. (1994) were able to reduce the number of kinematic variables to

analyze. They then modeled the shape pattern of these variables by a distortion

analysis to resolve d l distributed changes in the gait panems within subjects.

Loslever et al. (1994) have developed a combined statistical method to study gait

patterns which involved both principal component analysis and multiple

conespondence analysis. Holzreiter and K6hle (1993) applied artificial neural

network modeling techniques to distinguish between able-bodied and

pathological gait These advanced statistical methods are opening new and

promising horizons towards characterization of n o d and pathological gait

Chapter 4- (Paper I) : Women und men able-bodiedgair %

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Paper 2:

Functional gait asymmetry in bilateral able-bodied gait

This paper has been published in Human Movement Science Journal. 16 :243-258,1997.

FUNCTIONAL GAIT ASYMMETRY IN ABLE BODIED SUBJECTS

Heydar Sadeghi"-', Paul ~1lard"and Morris Duhaime"

'Department of Physical Education, University of Montreal, Montreal, PQ, CANADA

'Research Center, Saint-Justine Hospital. 3175 Cote Ste-Catherine, Montreal, PQ, CANADA

'Department of Physical Education, University of Tarbiat Moallem, Tehran, IRAN

'Orthopaedic Surgery, Shrinex's Hospital, Montreal, PQ, CANADA

Running headline: Functional gait asymmetry.

All correspondence should be addressed to Heydar Sadeghi Laboratoire d'Etude du Mouvement Centre de recherche Sainte-Justine Hospital 3175 Cote Ste-Catherine Montreal, PQ, H3T 1C5 CANADA Tel: (514) 345-4740 Fax: (514) 345-4801 E-mail: sadeghih@ere.umontrd.ca

ABSTRAm

Symmetry is assumed in unilateral gait studies or when pooling right and left limb

data. The purpose of this study was to identify which muscle powers and

associated mechanical energies were related to the support and propulsion

functions using Principal Component Analysis (PCX). Nineteen able-bodied male

subjects participated in this study. They were all right hand and leg dominant

Simultaneous bilateral threedimensional data were collected from an eight-

camera video system and two force plates. The PCA method was used to reduce

and categorize the peak muscle powers and mechanical energies calculated at the

hip, knee and ankle in each plane. Student's t-test for paired data was applied to

determine significant differences between the identified gait parameters. The

limb, which had a propulsion function, was characterized by a strong third hip

power at push off. Most of the parameters identified by the PCA were associated

with the hip, and were mainly in the sagittal plane. These parameters were

concentrated during push-off. There was a secondary suppon function, which

occurred during, midstance. For the S i b having a supporting function, most of its

activities were associated with the knee, and were spread throughout the stance

phase.

Keywords: Gait analysis Symmetry, Principal Component Analysis.

INTRODUrnON

Many gait anal-yses have focused on the biomechanical arpects of the right limb,

assuming similarity with the contralateral limb. Using b i d three-dimensional

e l ~ g o n i o m e t e r s in twelve able-bodied subjects, Hannah et aL (1984) have

shown joint motion symmetry between the hips in all three planes and at the knees

in the sagittal plane during natural walking. Hamill et al. (1984) found no

significant difference between the limbs in 11 vertical, 5 anterior-posterior and 4

medio-lateral characteristics of ground reaction forces in walking and running.

These results were later confinned by Menard a al. (1992). in a study where eight

normal subjects walked at their natural speed

However, there are a number of bilateral investigations where gait asymmetry was

documented. Rosenrot et al. (1980) reported that the duration of the initial and

terminal double support periods were not identical, as would be expected in young

healthy subjects. Crowe et al. (1993) reported a consistent asymmetry in the

oscillation of the body center of mass using ground reaction force data According

to Wheelright et al. (1993). gait asymmetry may be related to the position of the

foot during the swing phase, reflecting the subject's laterality. Though Gunderson

et al. (1989) concluded that asymmetry cannot be predicted by lateral dominance,

Ounpuu and Winter (1989) found some evidence to suggest that the plantar-flexor

electronyographic (EMG) activity be related to limb dominance. Arsmault et al.

(1986) also found asymmetries in EMG profiles

The aim of locomotion is to support the body a s a h gravity while generating

movements to propel the body forward. It requires precise coordination between

the tasks of propulsion, and balance wmter, 1990). In recent gait studies,

asymmetry has been explained by a functional behavior of iower extremities.

H i w a (1981) claimed that the left and right lower limbs have a supporting and

a moving function, respectively. For 53 males and 39 females walking at slow,

free and fast walking speeds, Hirokawa (1989) associated propulsion with the

right limb while the left limb was found to be responsible for support. Ailard et al.

(1996) were among the fim to report simultaneous bilateral three-dimensional

inverse d-c gait data in 19 able men. Asymmetries in the peak muscle

powers as well as in their corresponding energies were found. nough both S i b s

generated the same total energy, the higher total energy absorption in the right

limb was attributed to its control.

The functions of propulsion and control of the lower limbs have been clearly

identified during gait, but the biomechanical parameters associated with each of

them are still to be identified. Though temporal and phasic gait parameters, joint

angles and muscle moments may be used to characterize gait patterns, muscle

powers are more convenient since they lump both kinematic and kinetic

information To our knowledge+ there have been only a f w studies that dealt with

symmetry in simultaneous bilateral three-dimensional gait analyses.

The purposes of this m d y were a) to identify the three-dimensional peak

mechanical muscle powers and the mechanical energies developed by the lower

extremities d r k g able-bodied gait using Principal Component Analysis and b) to

determine which of theze gait parameters were related to propulsion and support.

METHODS

Nineteen healthy young adult men recruited from the Department of Physical

Education at the University of Montreal participated in this study. Their average

age and height were 2534.1 years and 1.77M.057 m respectively, while their

avmge mass was 80.6a13.8 kg. Subjects had no previous history of neither

orthopaedic or neuromuscular diseases nor recent injuries, which could affect their

walking, pattern. None had l i b length discrepancies. Subjects were right hand

and leg dominant as determined h m five activities, involving: 1) kicking a ball,

2) throwing a ball 3) writing, 4) opening a jar, and 5) hopping on a single l i b .

Swen body segments were defined, namely the trunk, the thighs, the shanks and

the feet, by means of 24 reflective markers having a diameter of 24 mm, to

identify the three-dimensional (3D) kinematics of the lower limbs. For the trunk,

a marker was placed over the lateral border of the shoulders, while markers placed

over the anterior superior iliac spine, crest of ilum and the greater trochanter

defined the pelvis. Markers were also put over the upper anterior and mid-lateral

sides of the thigh and others covered the head of the lateral epicondyle, and the

mid- and lower laterat sides of the shank. The feet were defined by three markas

placed over the laterat malleolug the heel and the laterat border of the fifth

rnetafarso-phalangeal joint. TxansfOrmation measurements were taken between

the external markers and the estimated joint center of rotation, to express the gait

parameters in the joint coordinate systan

Data collection was performed by means of an eightcamera video system (Expert

Vision 3D systm, Motion Analysis Corporation, Santa R o y California) and two

AMTI force plates (Advanced Mechanical Technology, Inc., Newton,

Massachusetts). Four cameras were placed on each side of the subject, at an

average &-tance of 4.5m along an arc of about 120 degrees, to cover two

consecutive strides. Force plates were located in the middle portion of a 13m

walkway. They were 150mm fium each other, to enable the subject to take one

step on each ofthem.

The subject were wearing wmfomble attire, including shorts and running shoes.

Atter camem calibration, they were asked to walk at a self-determined pace along

the walkway and step consecutively on each force plate. This procedure was

repeated until two other good trials were obtained. A trial was rejected if the

subject did not take a step in the vicinity of each force plate's center. The video

data were recorded at 90Hz while the synchronized force data were sampled at

360Hz

The Direct Linear Transformation was used in the Motion Analysis Expat Vision

software to raonstruct the image markers into three-dimensional coordinates.

Noise in video and force data was d u c e d by means of a fourth order -phase

lag Butteworth filter, having a cutoff fkquencies of 6Hz and 5OHz respectively

(Winter, 1990). The root mean square error of the 3-D coordinates was less than

5nun

The temporal and phasic gait parameters were determined from the force plate and

video data Initial contact and toeoff were determined from the vertical ground

reaction force while the ipsilateral subsequent heel-strike was determined from

video data

The inverse dynamic analysis solhare, K i n W provided by Motion Analysis

Corporation, was used to calculate the muscle moments at each joint throughout

the gait cycle. Instantaneous muscle powers (P) were calculated at each joint 6)

and in each plane Q as the product of the net muscle moment (M) and the joint

angular velocity (a).

P*=&.a*

Joint moments and angular velocities acting in the same direction resulted in

power genedon, whereas power absorption was obtained when the signs were of

different polarities. The energy or work (W) generated or absorbed at each joint

UloprerC (Paper MU): Flmcrionrrlarlmmary ... 110

(j). in each plane Q, corresponded to the area under the power curve (P). It was

calculated as

The muscle powas and their respective mechanical energies were normalized

with respect to body mass, and expressed in Wkg and Jkg respectively. The data

were also normalized with respect to the gait cycle (GC) having a mean stance

phase of 60.68+1.72% and 6151.51% for the right and lefl limbs respectively.

Left swing phase began at the end of the double supporf at the end of loading

response ofthe right limb gait cycle.

The power and energy bursts were labeled according to Eng and Winter (1995).

The first lener referred to the joint while the number indicated the sequence of the

burst A second letter identified the appropriate plane of motion For example

H3S corresponded to the third peak power or energy bunt of the hip in the sagittal

plane.

The Principal Component Analysis Statistical method was used to analyze the

t~mporal gait pameters, the peak powas and their related mechanical energies,

altogether 48 discrete values for each l i b and for each trial. Based on the Kaiser

criterion (Kaiser, 1960). factors with eigenvalues greater than one were retained

and the Principal Compzents (PCs) which contained at least 60% of the

information were kept (Statistics for window, 1994, Statfbft Technical Support by

Statsoft Inc, Tulsa). The D i t Varimax method was applied to categorize the

PCs according to the magnitude of each correlation coefficient Then within each

of the extmted PCs, the parameters having a factor loading (which reprrsents the

correlation coefficient between each item and its PC) of 0.6 and above were

compared by means of Student's paired t-test @ < 0.05). to determine the

significant differences between the right and left limbs.

RESULTS AND DISCUSSION

Temporal and phasic gait parametas are given in Table 1. The average walking

speed (131 mls), stride length (1.46 m) and cadence (107 stepshin) for both

limbs were comparable to those published in the literahue (Craik, 1995; Oberg et

al. 1993) for naNral walking.

Table 1: Temporal and phasic gait parameters of 19 able-bodied individuals.

Right limb Left limb Mean o Mean o

speed Ws) 130 0.12 1.32 0.10

Stride length (m) 1.45 0.07 1.47 0.07

Cadence (stepshin) 106.5 7.03 107.9 7.99

Stance (%) 60.7 1.72 60.9 1.50

The mean power curves developed at the hip, lmee and ankle for the right and left

l i d are presented in Fig. 1 and Fig. 2 rrspectively. These power pattems have

been dims& by Allard et A. (1996). Peak powers developed or absorbed in the

sadnal plane were in agreement with those reported by Eng and Wmter (1995)

and L o i a al. (1995). Differences with respect to published values were noted

for the peak powers in the bntal and transverse planes. This variability can be

accounted for in part by the polarity of the joint moments (Crowininshield et al.,

1978; Kadaba et al., 1989; Apkarian et al, 1989). AUard et al. (1996) alluded to

presence of different able-bodied gait patterns.

Chapter C (Paper MV): Funaionul agmmar)'... 113

Fig. 1. Powen developed at the right a) hip, b) knee and c) ankIe, during natural

speed walking in 19 able-bodied subjects. The vettical lies indicate the

beginning and the end of the double support period.

C.4, .-* R,

Fig. 2. Powers developed at the left a) hip, b) knee and c) ankle. during natural

speed walking in 19 able-bodied subjects. The left l i b gait cycle is overlaid on

right limb gait cycle, and begins at the 11% mark.

The first four-extracted Principal Components accounted for about 60% of the

observations found in the right and left limbs. For each PC, the parametem having

a factor loading of 0.60 and above are reported in Table 2, and grouped according

to whether they were common to both r i b s or related to either the right or left

l i b . These gait parameters were mostly related to hi.

The HIS and K3T bursts were the only common parameters to both limbs. The

HIS generation b m was associated with the control of the tnmk and the collapse

of the stance limb (Eng and Winter, 1995) as well as to forward progression (Allard

et al, 1996). This occumd as the thigh extended at 12% of the gait cycle (GC).

Both limbs generated about the same amount of peak powers and enagies

Table 2. Peak powers and energies common to both limbs and to the right and left

limbs.

Power (Wkg)

Right L i b Left L i b Mean o Mean a

Both limbs

HIS 1.50 1.10 1.23 0.99 K3T 0.07 0.07 0.05 0.16

Right S i b

H3S 3.02. 1.42 240' 1.53 H3F -0.19 0.14 -0.22 029 H2T - - - - K1S - - - - Left limb

HlF -0.81 033 -0.95 057 HIT -0.18 0.13 -0.17 0.17 K2S 0.45' 0.36 0.56' 0.53 U S - - - - KIF -0.12* 027 0.11' 0.16 K2T -0.12' 0.08 -0.07' 0.10 K3T 0.07 0.08 0.05 0.16

pc 0.05

Energy (Jkg 10'3

Right Limb Left Limb Mean o Mean a

The K3T power burst which occmed a! 55% GC was associated by Allard et al.

(1996) with an internal rotation of the thigh during push-off, in moving the body

center of mass towards the contralateral limb. Both limbs developed the same

peak powers

The factor loading of the muscle powers and mechanical energies of the right limb

ye presented in Fig. 3. Including the common HIS and K3T values, four peak

powers and four energy bursts charaaerized the right limb. Most of the peak

powers occurred in the sagittal plane, although transverse and frontal powers and

energies were also present

Fig. 3. Factor loading of the peak powas and mechanical energies of the right

S i b .

Chapter 4- (Paper MO): Fvncnbnd m)mmeny .- 118

All but KlS and H3F were generating. Most of the peak powers and energies

occurred at the hip, followed by some at the knee. Though significant differences

were reported between sides in the ankle energies (Allard et al, 1996), this

parameters did not appear in the factor analysis The PCA analysis revealed also

that the moa irnpomnt gait parameters of the right limb were related to

propulsion The H3S, H3F and K3T power bursts occurred essentially during the

push-off period. Right limb values were generally the higheq although only the

HjS activity was significantly different @ < 0.05).

Seven peak powers and eight energy bursts chYacterized the left limb, as shown in

Fig. 4. The peak powers did not occur principally in the sagittaI plane as for the

right S i b , but rather involved all three planes. There was as much absorption as

generation, and most of the activity occurred at the knee. This activity was spread

throughout the stance phase, rather than being concentrated in a specific period of

the gait cycle. The left limb had significantly higher values for HlF, K2S and

KlF, while the right limb generated more K3S energy.

Generally, the PCA has identified both the peak powers and their respective

energies to characterize the biomechanical behavior of the lower limbs. Most

often, significant ~fferences behveen the lower limb values were noted for both

types of parameters.

Fig. 4. Factor loading of the peak powers and mechanical energies of the left

limb.

Targeting a force plate during a gait assessment does not significantly affect the

ground reaction forces (Grabiier et al., 1995), but awareness by subject to take

consecutive steps on each force plate during data collection may have had an

influence. Furthermore, the subjects always stepped on the first platform with

their right foot This had the advantage of having the largest number of trials for

that single condition but at the cost of increasing the chances of obtaining gait

asymmetry. Our subjects were evaluated with their arms crossed over the chest, to

avoid occlusion of the pAd; x.5 hip markas. This may have influenced our

results, since asymmetrical arm action has the potential to compensate for

asymmetries elsewhere in the body (Hinrichs, 1992).

Chapm 4- (Paper m): Fmaional qmmeq). ... 120

Funhermore, a solidification process (Chez et 1995) did not correct the relative

displacements of the markers due to soft tissue motion Also, the mechanical

energies were calculated at each joint and for each plane from the respective

muscle powers, although powers and energies are scalar terms. Nonetheless, this

method was used by Eng and Winter (1995). as well as Allard et al. (1996), to

describe able-bodied gait and L o w et al. (1995) applied it to study patients

fined with total hip prostheses. The muscle powas and mechanical energies

determined h m the Principal Component Analysis will be discussed with respect

to each l i b , and then in term of asymmetry.

RIGHT LIMB

Our results bring further evidence for the importance of sadttal and frontal plane

actions during gait et al., 1990; Mackinnon L Witer, 1993), especially

for those occurring at the hip (Olney et al., 1995; Eng g: Winter, 1995).

The right limb generated the greatest powers and energies in the sagittal plane, and

most of their actions were developed during !b push-off period This propulsion

began with the right ankle plantarflexing (A2S = 3.21 Wkg) at 53% of the gait

cycle (GC), followed rapidly by a strong pull at the hip due to an H3S genmtion

(3.02 Wkg) at 58%GC. The hip pulled the thigh forward and controlled the

collapse of the pelvis on the contralateral l i b (H3F = -0.19 Wkg). While the

ankle pushed and the hip pulled, the right knee adjusted itself to ensure a good

Chapter 4- (Paperm): Funcdonal aqmmccay ... 121

pushaff. It flexed unda the extension moment (K3S = -0.14 Wkg) and

externally rotated (K3T = 0.07 Wkg), due to the ankle everting motion

The other hip @IS and H2T) and knee (KIS) actions were spread throughout the

midstance period, extending h m about 8% to 45% of the gait cycle. Considering

that they occurred during the contralateral limb swing phase and due to their

distant functional association, these powers appeared to be related to some form of

support function For example, HIS was associated with to the control of trunk

advancement (Eng and Winter, 1995). KIS controlled knee collapse (Winter,

1991). while H2T can cause the thigh to go into external rotation in prepantion for

the contralateral heel-strike.

Only the H3S power and its energy burst were significantly different The

asymmetry occurred in the push-off period, denoting a 20.6% stronger pulling

action of the right hip. Interestingly, the right S i b had a slightly faster walking

speed than that of the left side. Olney et al. (1994) explained that peak ankle and

hip powers at push-off were the most useful parameters in predicting stride speed,

for the unaffected S i b of subjects with hemiplegia Based on these obsavations,

as well as the concen!ntion in the push-off period of most PCA factors, and the

identification of many muscle power generation bursts, we therefore assume that

this limb's main function was that of propulsion, with a secondary action of

support, occuning during midstance.

LEFT LIMB

The left limb was characterized by a series of power and energy absorption and

generation peaks spread throughout the entire stance phase. These muscle

activities occurred in all three planes, and not mainly in the sagittal plane as for the

right limb.

At heel-strike, the hip was essentially active in a) controlling bunk forward

motion, b) contributing to the fo~ward propulsion by its HIS generation (123

Wkg), c) controlling the tru& rotation by its HIT absorption (0.02 Wkg), and d)

supporting the pelvis list on the contralateral side (HIF= -0.lOWkg). During

midstance and push-off, the knee provided a series of gait adjustments. For

example, the K2S power burst was restoring knee extension after its initial flexion

at the end of heel-strike and the K3S absorption peak compensated for the hip

pulling action and the ankle propulsion

Because of the controlling action of the hip during midstance and the known

passive role of the knee at push off, this limb had mostly a function of support

This was characterized by three strong controlling actions @IF, KIF and US).

A significantly lower K3S power absorption was atuiiuted to the reduction of the

knee action during push-off, in maintaining a walking speed similar to that of the

right limb.

LIMB ASYMMETRY

This 3-D simultaneous bilateral gait study supports previous studies (Arsemdt et

al, 1986; Herzag et al., 1989; Rosauot et al., 1980) where asymmetry was

documented. Our results, and those of Gunderson et al. (1989). challenge the

practice of conducting unilateral limb evaluations, or pooling right and left limb

gait data. Gait asymmetry in able-bodied subjects should not be considered as a

pathological phenomenon, but interpreted in terms of control and propulsion

strategies ( H i i w a , 1981; Hirokawa, 1989). However, no one has yet specified

which gait parameters were associated with each of these strategies.

Five parruneten were shown to be significantly different between the Sibs. For

the left limb, these occurred during heel-mike (HE), midstance (KIF, K2S) and

push-off (K3S). with the later being an absorption burst These were explained in

terms of control or stabilizing actions. For the right limb, there was only the H3S

generating burst, which occurred during push-off, delineating a propulsion

function

These results must interpreted with caution, since our subjects were all right-

handed and right-footed. The functional asymmetries might reflect limb

dominance of the subjects. Gunderson et al. (1989) and Yang and Winter (1985)

pointed out that averaging data across subjects tends to increase symmetry. Lack

of asymmetry may be explained in part by the choice of the of the proper gait

parameter. Gundason et al. (1989) used temporal and phasic gait parameters as

well as joint angles to quantify gait asymmetry. Hannah et al. (1984) concluded

&om kinematic data that able-bodied subjects walked with reasonable symmetry.

However, H m g et al. (1989) found gait asymmetries in force plate data to be

much larger than expected for a normal population We have selected muscle

power and mechanical energies, because they group both kinetic and kinematic

parameters, and these have been found by others (Olney et al., 1994; Loueau et

al., 1995) to be related to clinical findings.

CONCLUSION

The results supported the idea of a functional gait asymmetry. For the limb, which

had a propulsion function, characterized by a strong H3S burst. most of the

parameters identified by the PCA were associated with the hip and knee. These

were concenhafed during the push-off period. There was a secondary support

function, which occurred during, midstance. For the limb having a supporting

function, most of its activities were associated with the knee, and these were

spread throughout the stance phase. None of them was associated with

propulsion.

ACKNOWLEDGEMENTS

This work was funded in part by the Ministere de I'Industrie, du Commerce, des

Sciences et de la Technologic of Quebec (Programme Synergic), the Natural

Sciences and Engineaing Council of Canada and Les laboratoires d'ortheses et de

prostheses Medicus. The authors would like to thank the Ministry of the Cultural

and Higher Education and the Tarbiat Moallem University for their h c i a l

support to Heydar Sadeghi.

Umprer 4- (Paper two): Fwunonnl qmmeny ... 126

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Winter, D.A., 1990. Biomechanics and Motor Control of Human Movement

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Paper 3:

Muscle power relationship in bilateral able-bodied gait

This paper has been submitted for publication in the Physical Therapy Journal.

MUSCLE POWER RELATIONSHIPS IN BILATERAL ABLE-BODIED GAIT

Xeydar Sadeghi, "Paul Allad, and " Monk Duhaime

' Heydar Sadeghi, ThD., Research Assitant, Human Movement Laboratory, Research Center, Sainte-Justine Hospital, 3175 CBte-Ste-Catherine, Montreal, PQ, CANADA H3T 1C5 (sadeghih@m.umontreaI.ca). Address all corres- pondence to Dr. Heydar Sadeghi.

" Paul Allard, PhD., Professor, Department of Kinesiology, University of Montreal and Direcotr of Human Movement Laboratory at Research Center, Sainte-Justine Hospital.

"' Moms Duhaime, MD. Orthopaedic surgen and Professor in Orthopaedic Surgery, Shrinds Hospital, McGill University, 1529 avenue Cedar, Montreal. PQ, CANADA H3G 1A6.

Chapter 4- (Paper 3): Murclepowerrela~nship ... 131

ABSTRACT

BACKGROUW and PURPOSE: Although gait asymmetry in rehabilitation has

been documented, little is known about propulsion and control tasks performed by

each limb and how these tasks ar,. managed between the lower limbs. The

purpose of this study was to test that limb propulsion is mainly associated with the

interaction of a number of muscle power bursts developed throughout the stance

phase while control actions are mainly achieved by the contralateral limb through

a different power burst interactions. Furthermore, we hypothesize that the power

activities of a limb are related to those of the conha-lateral l i b . MIX-IOD: The

gait of nineteen right handed and leg dominant subjects was assessed using an

eight camera video-based system synchronized to two force plates. The muscle

powers and their related mechanical energy were calculated at each joint and in

each plane of the lower limbs by means of the inverse dynamic technique. The

principal component analysis method was applied to reduce and classify 54 gait

parameters for each l i b while the Pearson correlation method was used to

determine the interaction among each limb data sets. Furthermore+ Canonical

Correlation Analysis was performed on the reduced data to establish the best

linear correlation equation between the right and left limb data sets. RESULTand

CONCLUSION: Gait propulsion was an activity initiated by the hip shortly after

heel-strike and maintained throughout the stance phase. These results do not

support the hypothesis that the ankle was a major wntnbutor to fonvard

progression Control was the main task of the left limb as evidenced by the power

Chapter 4- (Paper 3): MurclepowerreI&nrhip ... I32

absorption bursts at the hip and knee. The left limb power genedons were

generally secondary to control activities and were posbly involved in correction

adjustments of the other limb's propulsion. Canonical Correlation Analysis was

used to determine the intaactions between the right and left lower extremity gait

data sets. Inter-limb intaaction fuaher emphasized the functional relationship

between fonvard p r o m o n and control tasks developed by each limb and

highlighted the importance of the hn ta l and transverse plane actions during gait

Key word: Biomechanics, Gait analysis, Gait symmetry, Muscle powers.

IMRODUCnON

Gait analysis of able-bodied subjects are performed to chamcterize the normal

gait functions and provide a better undastanding of the underlying musculo-

skeletal disorders in order to improve the rehabilitation outcome. For example,

joint motion can be used to descni systematic differences between gait cycles in

able-bodied subjects'. Ground reaction forces and their related impulse were

used by Prince et al.' to explain running gait asymmetry in below-knee amputees

while DeVita et al? have shown in patients with an anterior mciate ligament

deficiency how muscles moments were affected by functional bracing. Muscle

powers which combine both kinetic (moments) and kinematics (angular velocity)

information were used to describe the gait of able-bodied subjects'. ', amputeesb

and patients fitted with a total hip prosthesis7. Muscle powers appear to be a

good indicator of the person's ability to propel and control their lower l i~nbs~.~.

Our undRstanding of able-bodied locomotion improves by -dying the

interaction among biomechanical gait descriptoa. Coordination in walking was

observed by Lasko et al!Owho repofled a strung cross-correlation for hipknee,

knee-ankle and hipankle rotations. Using a stepwise regression, Olney et al?

were able to identify and relate the ternpod, kinematic and kinetic variables to

walking speed in both able-bodied subjects and patients with hemiplegia

Andrews et aL" performed a complete radiographic, video and force plate

evaluation to establish the relationships between bone alignment of the lower

Chapter 4- (Paper 3): M d e power re!ariomhip ... 134

artremities, foot progesion angle and knee adduction moment A significant

correlation was found between valgus limbs and out-toeing gait The above

studies were essentially limited to the interaction of various gait parameters within

the same limb segment Little is known about the behavior of these parameters in

the contralateral limb and the bilateral L i b interaction

Bilateral gait analyses have principally focused on the similarity or differences

observed between limbs. For example, Hannah et al." have shown joint motion

symmetry between the hips in all three planes and at the knees in the sagittal plane

during natural walking while Hamill et al!' found no significant difference

between the limbs in ground reaction forces in walking and running. Though

these studies suppoa symmetry in gait, differences in some gait parameters also

have been documented in able-bodied subjects. Herzog et al." found that

asymmetries in 34 ground reaction force data were much larger than expected for

a control group. Variables such as maximum vertical forces showed unexpected

large limits of normal asymmetry even though these values had large magnitude

and high reliability for one leg. Gunderson et al." have also documented gait

asymmetry in temporal and kinematic parameters and challenged the assumption

made by investigators that right and left legs present symmemcal outcomes.

Gait asymmetry was attributed to slight variations in measurement systedb, limb

dominar~ce'~ and to differences in limb function1'. Though footedness has been

Chap~er 4- (Paper 3): Muscle power reIationrhip ... 135

identified, gait asymmetry could not be predicted by lateral dominance".

Nonetheless, asymmetries, however, in able-bodied subject gait were associated

with propulsion by one limb and support by the other1'. Unfortunately, these

studies usually focused on a single parameter at a time. Recently, Sadeghi et

al? found that fonvard propulsion was related to the leg mostly characterized by

muscle power genemion whereas support and control functions were associated

to a limb having a predominantly power absorption behavior. However, they did

not show the relative importance of the muscle powers within each l i b or l i b

interaction

Few if any, have assessed asymmetry using several gait parameters in a single

analysis although the statistical tools are available. Loslever et al." used the

principal component analysis (PCA) with joint angles measured in the sagittal

plane and ground reaction force to classify able-bodied gait patterns. Using a

similar approach, Yamamoto et al? normalized and quantified the bilateral gait

pattern of 21 1 patients with hip diseases. While, recently Ohey et al." used

the PCA as a means of reducing redundant information presented by 40 gait

parameters.

The PCA could also be used to assess gait asymmetry in able-bodied subjects

while Canonical Correlation Analysis could be used to compare right and left

limb data sets. The Canonical Correlation Analysis has not yet been used in

gait analysis although it was applied in other research fields such as in the

determination of how job strains affect the psychosocial factors associated with

risk increase of cardiovascular disease?'.

We postulate that gait asymmetry in able-bodied subjects can be explained in

terms of actions taken by the lower limbs to propel the body segments and to

control their fonvani progression The muscle powers developed within a limb to

accomplish control and propulsion tasks and the muscle power interactions

between the limbs are responsible for the observed functional gait asymmetry.

The purpose of this study was to test the concept that limb propulsion is mainly

associated with the interaction of a number of muscle power bursts developed

throughout the stance phase while conml actions are mainly achieved by the

contralateral limb through a different power burst interactions. Furthermore, we

hypothesize that the power activities of a limb are related to those of the contra-

lateral limb.

METHODS

The nineteen healthy adult men participating in this study had an average age

and height of 25.3i4.1 years and 1.77W.057 m respectively, while their

average mass was 80.e13.8 kg. Subjects had no previous history of orthopedic

ailment such as a recent injury or surgery, which could affect their walking

Chapter 4- (Paper 3): Murcle power reIatiomhip ... 137

pattern. Subjects having limb length discrepancies of 0.5cm or more were

excluded from this study. All subjets were right hand and leg dominant as

determined &om five activities involving: throwing a ball, writing, opening a jar,

kicking a ball and hopping on a single S i b . Although this paper does not focus

on limb dominance, we wished to have a uniform population in case dominance

made a difference.

DATA COLLECTION

Body segments were defined by means of twenty reflective markers having a

diameter of 2.5 cm. For the foot, markers were placed over the lateral malleolus,

the heel and the lateral border of the f i f i metatam-phalangeal joint, while

markers were placed over the apex of the lateral epicondyle and the mid lateral

sides of the tibia to locate the shank. Markers were also put over the mid-lateral

sides of the thigh and the greater trochanter. For the pelvis, markers were put over

the anterior superior iliac spine and crest of ileum. Markm of the pelvis as well

as those puts over the lateral border of the shoulders identified the trunk. To

calculate motion in the joint coordinate system, measurements were taken

between the external markers and the estimated joint center of rotation.

Bilateral kinetic gait data were collected by means of two AMTI force plates'

centrally located along a 13m walkway and an eightcamera video sysiemn. To

cover two consecutive strides, four camem were placed on each side of the

subject, at an avenge distance of 4.5m and located along an arc of about 120

degrees.

AAer camera calibration, subjects wearing comfortable shorts and running shoes

were asked to walk along the walkway at their own fire walking pace. Video

data were recorded at 90 Hz while the synchronized force data were sampled at

360 Hz Although data were collected for five walking trials, the three bilateral

gait trials closest to the subject's mean walking speed were selected for

analysis.

The Direct Linear Transformation software of the Motion Analysis Expert Vision

system was used to recomtmct the image markers into three-dimensional

coordinates. Noise in video and force data were reduced by means of a fourth

order zero-phase lag Butterworth filter, having a cut-off fitquencies of 6 Hz and

30 Hz respectivelf. The root mean square absolute error of the 3-D coordinates

was less than 5 mm while the relative error measurement corresponding to the

distance between two known markers was less than 1 mm.

-

'Advanced Mechanical Technology, Inc., Newton, Massachusetts.

Chapter 4- (Paper 3): Muscle power relationship ... 139

DATA ANALYSIS

The temporal and phasic gait parameters were determined fmm the force plates

and video data. Initial contact and toe-off were determined from the vedcal

ground reaction force while the ipsilateral subsequent heel-strike was

determined fmm video data.

Body segment parameters, kinematic and force plate data were used in an inverse

dynamic approach to calculate the net muscle moment at each joint throughout the

gait cycle. Instantaneous muscle powers, P were calculated at each joint, j and in

each plane. k by the product of the net muscle moment, hf and the joint angular

velocity, o . The powers were expressed as

P,=E/L.o, (1)

Joint moments and angular velocities acting in the same direction resulted in

power generation; whereas, power absorption was obtained when the polaities

were opposite. The mechanical energy, W generated or absorbed at each joint

was calculated fmm the m u l e powers developed in each plane by

W,= ~P,.dt (2)

For averaging purposes, muscle powers and their respective mechanical energies

were normalized with respect to subject's body mass. The data were also

normalized with respect to the duration of the gait cycle and by fixing the stance

"Expert Vision 3D system, Motion Analysis Corporation, Santa Rosa, California

phase at the mean value of 60.7+1.7% for the right limb and at 61.&15% for the

left Although this difference in the relative stance phase duration could reflect

the sampling rate of the video-system, the stance phase were not found

statistically significant. The power and energy bursts were labeled according to

Eng and Winter'. The first letter referred to the joint while the number indicated

the sequence of the power burst. A second letter identified the appropriate plane

of motion For example H3S comsponded to the third peak powcr or energy

burst of the hip in the sagittal plane. In all 44 peak muscles powers and

mechanical energies as well as ten phasic parameters were calculated for each

limb.

STATISTICAL ANALYSIS

Principal component analysis (PCA) as a da!a reduction and structure detection

method was performed to identify and classify the 54 gait parameters for each

limb into a smaller data set called Principal Component (PC). The reader is

referred to OIney et al.= for a detailed clinical example of the PCA method. In

this study the first four PCs which contained over 60% of the information based

on the Kaiser c~iterion'~, were kept Then within each of the extmted PC, the gait

parameters having a factor loading which express correlation between the PCs and

the parameters of 0.6 and above were selected for !kther analysis.

Chapter 4- (Paper3): MtrvlepowerreIeabnship ... 141

Pearson correlation analysis was carried out to determine the interactions between

all parameters calculated within each limb throughout the gait cycle. Correlations

higher than 0.60 were kept. F i y , Canonical Correlation module was

performed on the reduced data sets to establish the best linear correlation equation

between all the right and left limb limbs during natural speed walking.

The easiest way to understand Canonical Correlation method is to think of

multiple regression. In regression, there are several variables on one side of the

equation and a single variable on the other side. These variables are ccmbined

into a predicted value to produce the highest correlation between the predicted

value and the single variable. For example, speed of walking could be predicted

by cadence, stride length. body heighr In Canonical Correlation, there is a set of

variables on each sides of the equation. For each set, the variables are combined

to produce a predicted value that has the highest correlation with the predicted

value on the other side. For example, speed of walking, body height, age are

related to cadence, stride length and stride length. Furthermore, in multiple

regression, there is only one combination of variables because there is only a

single value to predict on the othcr side of the equation, while in Canonical

Correlation many combinations are expected, since there are several variables on

both sides to relate them to each other. Although there are potentially as many

ways to recombine the variables, as there are variables, usually only the first or

two or three combi ions are reliable and need to be interpreted. These

Chnper 4- (Paper 3): MuscIe p o w relationship ... 142

combi ions are known as Canonical Root In this study, the first CR which

presented the most significant cornlation coefficient between the weighted sum

scores of the right and left set of the data, was discussed (R = 0.83, p<0.0001).

All statistical analysis was pertbrmed using Statistics sofhvareQ.

RESULTS

To illustrate the 3-D muscle powers developed during the gait cycle and to

identify the peak values, which were selected for analysis, the mean left limb

curves are overlaid on the mean right limb values and standard deviation values as

shown in Figure 1. These curves were reported and discussed by Allard et al.'"

and generally correspond to the values reported by Eng and Winter4.

When performing a PCA analysis, it is suggested to eliminate the redundant

parameters but that is not required. Nonetheless, a correlation analysis was

performed on all the 54 parameters and that for each S i b prior to applying the

PCA. The swing phase duration, which was highly correlated with that of the

stance phase (0.90) was omitted from, funher analyses. Speed and cadence

(0.72 right limb and 0.75 left Sib) , speed and step length (0.71 right limb and

0.63 left limb) and double support duration and stance phase duration (0.59

right limb and 0.79 left limb) were weakly to moderately correlate. These

parameters were not rejected.

' StafSOh hc. Tulsa OK USA.

Figure 1: Mean three-dimensional a) hip, b) knee and c) ankle muscle power

curves developed a! the right (solid Sine) and the left lower S i b (dash line) by 19

able-bodied subjects for 57 natural speed gait trials. The overlaid dashed line

represents one standard deviation &om the mean for the right limb muscle power.

Chapter 4- (Paper 3): Musclepower relationship ... I44

Since energy values correspcnd to the area under the power c u r v e a strong

correlation between them was expected. Many of these correlations were above

0.9. For example, the A2S power had a correlation of 0.87 with its

corresponding energy. However, low correlations also were found since peak

powers do not take into consideration the shape of the power burst (0.1 1 for the

H3S). For example, a phcular peak power could have a similar value for each

limb but the time of application could vary and therefore, the mechanical energy

associated to that power burst could indicate a functional asymmetry in gait.

Considering, that some powers were highly correlated with their mechanical

energy while others were not, all power and energy parameters were arbitrarily

kept for further analysis.

The factor loading of the significant tenlporal, power and energy parameters

derived h m the PCA of the right and left limbs are respectively presented in

Tables 1 and 2. For the right S i b , the significant gait parameters shown in

Table 1 were mostly related to the hip activity. Six of the nine gait parameters

derived h m the PCA were associated with power generation. Walking speed

and step length were identified by the PCA, though no significant differences

was noted between limbs.

Chapfa4- (Paper3): Mudepowerre]orionship ... I45

Table 1 Right limb factor loading of the significant, peak pow- mechanical

energies and temporal parameters with their corresponding standard

deviations in parenthesis.

Right L i b

HIS

HIS

H3S

H3S

H3F

H2T

KlS

K3T

Speed ( m 4

Factor Muscle

loading powers

OYncg)

0.86 150 (1.10)

0.77

0.74 3.02 (1.42)

0.78

0.83 -0.19 (0.14)

0.83

0.73

0.52 0.07 (0.07)

0.71

Eoagy Temporal

(Jkg 109 parameters

The let? limb (Table 2) was mostly characterized by absorption and generation

bursts that were about equally distributed between the hip and knee in all three

planes. Since the PCA did not identify any parameters associated to the swing

phase (Tables 1 and 2). our discussion will be essentially limited to the stance

phase.

Only the HIS and the K3T parameters w m common to both limbs. The HIS

burst was considered by Vardaxis et al.% and Allard et al.' has a power generation

burst that contributes to limb pmgression Thus both leg are propelling. By a

Chapter 4- ( P u p 3): Muscle power relnrionship ... I46

K3T pow= genetation, the shank which was internally rotating while the knee

was flexing during push-off contriiuted actively to body-weight transfer.

Table 2 Left limb f w r loading of the significant peak powers, mechanical

energies and temporal parameters with their corresponding standard

deviations in parenthesis.

Left Limb

HIS

HIS

HIF

HlF

HIT

HIT

K2S

K2S

K3S

KIF

KIF

K2T

K2T

K3T

K3T

Step length

(m)

Factor loading

0.81

0.73

0.80

0.79

0.60

0.60

0.70

0.74

0.73

0.87

0.85

0.73

0.68

0.89

0.89

0.75

Muscle

pow=

(wkg)

1.23 (0.99)

-0.95 (0.57)

-0.17 (0.17)

056 (053)

-0.1 1 (0.16)

-0.07 (0.10)

0.05 (0.16)

Enagy Temporal

(Jkg 1W7 parameters

The Pearson correlation method was applied between all pairs of the gait

parameters l i e d in Table 1 and Table 2, separately, to determine how their

interactions contribute to forward progression and control, respectively. For the

right limb, four parameters had a Peanon correlation coefficient of 0.6 or

above, while for the left limb they were five (Table 3).

Table 3: Pearson comelation coefficient values for the right and left lower

limb peak powers (P) and mechanical energies (E).

Left Limb

K2S Q

(PI K2.r (E)

K2.r 0') K3-r 0') K3T 0')

The correlation for the first Canonical Root between the right and left Sib data

sets is shown in Figure 2. This scatter plot indicates a high positive linear

contriiution of the weighted values having a coefficient canonical rwt of 0.83 (p

< 0.001).

Ulpprer 4 (Poper 3): Mvrclepower relationship ... I48

Figure 2: F i t canonical correlation for the right and left l i b data set having a

coefficient canonical root of 0.83 @<0.001).

3

2 .

C 2 1 : C . crr V ' a E 0 . - - . L s : 0 -1 C ) . .e 0) 3

-2

3

This supports a strong relation between the attributed functions of right limb

propulsion and left limb control measured in hrro consecutive steps. The

0

.

. 0 0 0

- .

canonical loadiig values of the first canonical root are given in Table 4 for the

right and left limbs. These values reflect the relative importance of each

3.5 -25 -1 .5 0.5 0.5 1.5 25

Right lower limb data set

parameter within a data set with respect to those of the conhalateral l i b .

Chapter4 (Paper3): .V~~(depowreIan'O~hip ... 149

Table 4: Canonical facton of the right and left limbs using the kght gait peak

power (P) and mechanical energy Q of the right limb and the 15 of the left limb

Canonical Value

0.18

0.30

0.12

0.08

-0.21

-0.25

-0.62

-0.58

0.02

0.26

0.22

0.03

0.00

-0.56

-0.58

-0.80

Generally, a high loading factor value was associated to the right hip and left

knee parameters. Furthermore, the HIS, H3S and the H2T right limb

parameters were all generating energy and closely associated to the propulsion

task of the lower extremity. Speed and stride length displayed a high factor

loading. Since the left limb was mostly responsible for control, the right limb

Chapter 4- (Paper3): MuscIepoww rekuionrhip ... I50

s p e d loading factor was negatively and strongly associated (-0.70) to the left

limb performance. Liewise, left limb step length was also strongly (-0.80)

related to the right limb that is assumed to be mostly propelling the body

fonvard.

DISCUSSION

The main objective of this study w a to test that limb propulsion is mainly

associated with the interaction of a number of muscle power bursts developed

throughout the stance phase while control actions are mainly achieved by the

contralateral limb through a different power burst interactions.

The ankle power generation burst developed at push-off (A2S) was not selected in

the first four Principal Component of the PCA as a key parameter for either Sib.

This was somewhat surprising. During push-off, it was assumed that the foot was

propelling the leg forwardz' while the thigh was pulling it'. " by the H3S power

generation burst Nonetheless, the A2S did appear in PCA but for the right limb

only in the f i f i PC, which explained less than %I0 of the total variance.

Although the A2S had the highest peak power value (3.21+/-0.69 Wkg) and a

comparable mechanical energy to the H3S (29.60 I@+/-17.90 Jkg), the A2S

did not display a gwd correlation with respect to other parameters. The

absence of ankle parameters is not due to a high correlation with other gait

parameters. For the light S i b , the highest correlation that either the ankle

push-off power (A2S) or energy had was 0.68 and it was with the AIS power

parameter. With a non-ankle parameter, the highest correlation of the A2S was

-0.56 with the H3F power. This was only a weak correlation, which implies it,

as the result of the ankle push-off there is less of a need for the hip adduction

moment to control passive abduction motion in pre-swing. The AIS power was

not identified in the first four PCs, however, the H3F power was. These results

confirm in part the observations of P f l . According to Peny"' the high

p m d reaction forces are not due to a strong push-off by the ankle but rather to

a reaction moment resulting from the displacement of the center of pressure

which moves anteriorly to the metatarsal heads leading to heel-off.

Right l i b power interaction

The peak muscle power HIS and its related mechanical energy which occurred

shortly after heel-snike were associated with the control of the forward

acceleratim of the and the potential collapse of the stance S i b 4 while

contributing to fonvard progressionS. '. The HIS was moderately correlated (r =

0.60 and 0.61, p c 0.001) with the hip flexor energy (H3S). The H3S activity

occurred at the end of the stance phase and was assumed by Winter et al? to pull

the thigh upwards. The intemction between the HIS and H3S can be explained in

part by the fact that they both contribute to forward progression.

Choper4- (Paper 3): Muscle power relationship ... 152

W1ntei5 presumed a relation between the HIS and H3S power generation's bunts

when he reported that the sagittal extensor moments were conhiiuting to propel

the body forward. Our results confirmed this obemation while revealing another

dimension that involved the pelvis during midstauce. The highest correlation was

found between the HIS peak power and the mechanical energy generated at the

hip (H2T) which occurred during the second half of mid-stance (r = 0.93, and

0.60, p < 0.001). During this time, the pelvis was rotating forward and bringing

the contralateral l i b fonvards under the H2T influence and therefore contributed

to the progression of the trunk. The energy associated to H2T power activity

which occurred during mid-stance was related to hip mechanical energy generated

(H3S) at the end of the stance phzse during the push-off period (r 4.61, p <

0.001). Pelvis rotation was recognized by Saunders e! al." as one of the six gait

determinants. They suggested that the pelvis being a rigid structure, contributed to

forward progression by its alternate rotations about each hi? (H2T). Moreover,

this finding supports that both pelvis rotation and hip extensor serve to effectively

lengthen the limb and reduce excessive drop of the body center of mad",

smoothing its vertical translation3'. From these observations, we can assume that

gait propulsion is not limited to the push-off period. It is an activity, which was

initiated shortly after heel-strke (HIS), maintained during midstance (H2T) and

completed at push-off by the H3S. Greater pelvis stability was provided by the

HIF and leads to an improve forward progression. Pelvis tilt was also recognized

Qtopter 4- (Paper 3): Muscle p e r reImonship ... 153

by Saunders et al?' as one of the gait detaminants reducing the vertical uunk

oscillation

The hip power absorption developed in the hn ta l plane at heel-strike (HE) and

throughout midstance was negatively correlated with the H3S (0.60, 0.001).

The H1F was assumed by Allard et al.'and M a c h o n and Wintd' to conmlled

the pelvis tilt as the left l i b enters the swing phase. During rnidwnce, the hip

contributed to forward progression by propelling the limb forward through the

HIS while s t a b i l i g pelvis tilt by the HlF.

Considering the strong hip activity interactions and the absence of ankle power or

energy parameters in the PC& these results support the passive role played by the

ankle in propelling the lower l i b forwad". These results can explain in part the

observations of Wagner et al? and Prince et & where similar ground reaction

forces were reported in lower-limb amputees fined with the SACH foot and some

energy storing foot prostheses.

Left limb power interactions

The hip HIS power generation which is considered as a source of propulsion was

moderately correlated (I = 0.60, p < 0.001) with the knee power g e n ~ d i o n in the

sagittal plane (K2S) as shown in Table 3. This K2S was assoCiated by Witer et

al" to knee extension following a flexion controlled by the extenson during early

midstance The K2S can be considered as a propeller but its conhibution is less

effective because its primary function was to extend the knee and to prepare the

lower limb for push-off.

The hip power absorption developed in the hn ta l plane at heel-strike (HlF) and

throughout midstance controlled the pelvis tilt as the right limb enters the swing

phase5.'" The moderate association between HIF and K2T (r = 0.60, p ~0.001)

linked together activities related to the control and preparation of the right S i b

heel-strike. Prior to the double support period, pelvis tilt was controlled to ensure

a safe body-weight transfer. Once the initial ground contact was made and the

right S i b was beginning to safely bear weight, the left knee was rotating

inwardly conhiuting to a progressive body weight transfer under the control of

on external rotation moment (K2T).

The internal rotation of the left shank actively contributed to body-weight transfer

by a K3T power generation 'Ibis is supported in part by a reasonable negative

correlation between the KZT and K3T (r = -0.60. p < 0.001) and a high negative

relationship was found between HlF and K3T peak muscle powers (r = -0.71, p <

0.001). Thus, the relationships between H1F. K2T and K3T powers can be

explained in terms of control actions by the lower left limb. These findings

confirm Winter et al=9 where they suggested that W e r s e knee moments are

passive elements which reacted to the hip moments.

This description of controlled body-weight tmnsfer may be applicable to both

limbs, but the interactions between these hips and knee powers were not found for

the right S i b . This can be explained in part by m n g right limb propulsion

While the left limb was in the swing phase, it may have deviated h m the body

path of progression by the right S i b push-OK A correction by the left l i b could

only be achieved during its own push-off period by the K2T and KiT power

bursts where the shank was internally rotating and orienting the trunk and the

lower l i b in line with the intended path of progression

The left limb revealed interactions between power generation and absorption

bursts. These absorption powers were mainly associated with the control

actions of the lower limb during the midstance and push-off periods. When

power generation activity was present, propulsion was mostly secondaq to

control activities and possibly occurred to correct actions resulting from the

right limb propulsion. These, however, are sufficient to propel the left limb

forward at about the same speed (1.32 d s i0.10) as the right limb (1.30 d s

~0.12) but by different means.

In a paper by Aissaoui et al." on the work done by the internal forces, the index

developed by Mansour et al." to calculate gait efficiency was applied

throughout the gait cycle. The IECC (hbntaneous Energy Correlation

Coefficient) is based on the calculation of potential and kinetic energies of the

Ciaprer 1 (Paper 3): Muscleponrrrelationrhip ... I56

segments that of the center of mass. In the double support period, the IECC fell

abruptly to a value near zero, indicating total loss of the conservation of energy.

This can reflect the dual actions of control and propulsion, which occur during

the double support period. For example, both the generation by the HIS and

absorption by the HIF were occurring at the left hip shortly aAer heel-strike.

Control and propulsion activities can occur during the double support at a

greater cost of energy resulting in a loss of energy conservation

Interaction between the limbs

Several investigators studied gait a s y m m e e ""3 However, most of them

expressed gait asymmetry by the difference between the right and left l i b values

or in terms of a ratio. Studies that concentrated on the relatio~hip between the

right and left gait parameters were limited to a planar anal& and often the data

were derived h m independent right and left l i b trials". Sadeghi et al'

attributed gait propulsion to the l i b which mostly displayed power and energy

generations The contralateral limb while still propelling was assumed to be

controlling f o d progression because many of its power and energy activities

were in absorption and those that were in generation contributed also to limb

suppoh However, they did not discuss the interaction between the Sibs.

Propulsion by one limb and control by the other were athiiuted by establishing

relationships between peak powers and their associated mechanical energies

developed within each limb. In an attempt to explain how these tasks were

modulated during natural speed walking a canonical cornlation analysis was

paformed on the left and right limb data sets. These data sets were obtained from

the PCA analysis, which performed on the right and left limbs and is reported in

Tables 1 and 2.

This hip contribution to propulsion was observed in the within S i b analysis

and previously recognized by Eng and Winter: Olney et al."' and Winter et a].>.

Though left limb K2S and KIF powers were also generating energy, they were

characterized more as a process of control rather than propulsion by Meglan and

Toddfs and Sadeghi et al." as well as in this study. The results of the canonical

correlation analysis further emphasiied the functional relationship between

forward progression and control tasks developed by each limb and highlight the

importance of the frontal and transverse plane actions during gait' 3"03.

Though right limb propulsion and left limb control tasks may be either purely

coincidental or due to limb dominance, interlimb dependency was well

demonstrated.

It is important to understand that this paper does not focus on S i b dominance in

able-body gait but rather on normal gait variations that we considcr as being

functional adaptations during two consecutive strides. Only right-footed subject

were selected since data from both right and left footed subjects could have

Uurprer 4- (Paper 3): Mtrrclepwer relationship ... I58

influenced the results due to l i b dominance. Furthermore, they represent a

larger population than left footed individuals. Thus, it is important to clearly

state that all subjects were right footed. Footedness is important to be identified

but with the available information its relation to gait asymmetry has not yet

been established. Gunderson et a1.15 where they concluded that asymmetry

cannot be predicted by lateral dominance confirms this. Considering that one

limb functionally behaves differently from the other and considering that we do

not have sufficient information to associate these differences to limb

dominance, we only wish to express our results in terms of one limb with

respect to the other in right footed subjects. The interactions between these gait

parameters within and between the limbs need to be addressed and to improve our

understanding of forward progression and control tasks in the lower extremities

during able-bodied walking.

CONCLUSION

The purpose of this study was to demonstrate that propulsion of the lower limb

was sociated to the interaction between muscle power bursts developed

throughout the stance phase while control was mostly achieved by the

contralateral limb. For the right limb, propulsion was an activity initiated by

the hip shortly after heel-strike and maintained throughout the stance phase.

These results do not support the hypothesis that the ankle is a major contributor

to forward progression. Control was the main task of the left l i b as evidenced

&prm 4- (Papm 3): Muscle ponw re[an'onship ... 159

by the power absorption burns. The left limb power generations were generally

secondary to control activities or possibly to colrect for the right limb

propulsion. Inter-limb interaction further e m p h a s i i the functional

relationship between forward progression and control tasks developed by each

limb. Furthermore, our result highlighted the role of the transverse and h n t a l

planes actions during gait which would be important to take it in account by

gait clinician and physiotherapists through the gait evaluation, rehabilitation as

well as treatment.

ACKNOWLEDGEMENTS

This work was funded in part by the MICST (Synergic) of Quebec, NSERC and

Medicus (Montreal). The authors would like to thank the Ministry of the Cultural

and Higher Education and Tarbiat Moallern University in IRAN to financial

support of Heydar Sadeghi.

Chapter 4- (Paper 3): Mxudepowr relationship ... I60

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36 Mansour, J.M., M.D. Lesh, M.D. Nowak and S.R Simon, 1982. A three-

dimensional multi-segmented analysis of the energetics of normal and

pathological gait. JBiomech 15.51-59.

37 McFadyen BJ. 1994. A geometric analysis of muscle mechanical power with

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38 Meglan, D. and F. Tot.& 1994. Kinetics of human locornorion. Chapter 4.

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and Wilkins publisher. 73- 99.

V - General Discussion

5. Introduction

Gait studies are of interest and are applicable to clinical evaluations,

diagnostic, rehabilitation, artificial limb designs as well as to robotics. Although

examination of human gait has received considerable scientific attention many

topics remain unclear and several questions are still utvnswered. This is due in

part to the three-dimensional nahlre of locomotion, the number of body segments

and muscles and the multitude af gait parameters.

So far, many attempts have been made to characterize, classify,

standardize and to identify the relevant gait parameters which play an important

role during locomotion (Sadeghi et al. 1997.. Mah et al. 1994., Wooten et al.

1990). In this %ad, many questions have been raised such as. Is there any

specific pattern, which could be used as a standard to represent able-bodied gait?

Do the lower limbs behave similarly during walking? Are there any interactions

between gait parameters developed at the different joints that could influence

lower limbs functions? Does lareality influence the tasks of the lower extremities

in able-bodied gait? Are the lower extremities' behaviors predictable? This thesis

was oriented to deal with some of these unanswered questions.

The first objective described in the published book chapter dealt with

the simultaneous bilateral muscle moments and mechanical powers to identify

the gait panem of able-bodied subjects. This lead us to an improved

understanding of the three-dimensional aspects of gait and in doing so, it brought

us one step further in the standardization of the gait pattern. The objectives

which have been investigated in the second paper were a) to identify the relevant

three-dimensional peak mechanical muscle powers and the energies developed by

the lower extremities during able-bodied gait and (b) to determine which of these

gait parameters were related to propulsion and support. In this regard, gait

asymmetry was identified and i n d u c e d in terms of the functional tasks

amibuted to the differences between the right and left lower limbs' values. The

third paper described the interaction between the limbs to better understand the

main tasks of lower extremities in able-bodied gait

Several issues related to the above objectives are first discussed. Then

the limitations of this study are followed by a retrospective analysis on this

research while future developments and recommendations complete this chapter.

In all analyses P < 0.05 for a power of 0.90.

5.1. Issues

The principal issues that can be expressed with respect to evaluating the

objectives ofthis study are discussed in the following.

5.1.1- Asymmetry influence on the standardization

of able-bodied gait pattern

Many attempts have been made to characterize and standardize able-

bodied gait (Allard et al. 1996, Kadaba et al. 1989.. Ehg and Winter 1995.. Mah

et al. 1994). However, the variability of gait data, even among normal subjects is

well known (Lasko-McCarthy et al. 1990., Winter, 1980.. Loslever et al. 1994).

To a cemin degree one's gait panern is due to one's individual nature (Inman

1980). There is also evidence that variability in gait increases with agc (Dobbs et

al. 1992.. Winter et al. 1990). Furthermore, the use of different experimental

protocols, terminology and instruments and low mtistical populations, has

l i t e d the interpretation of lateral gait studies.

As medical technology advances, the assessment of complex tasks such as

walking is becoming easier. Today's gait analysis laboratory provides the

essential tools for the quantification of able-bodied and pathological gait panem.

Quantitative gait analysis includes the set of methods and techniques and

provides information about human functional movement that is beyond the

Chapter 5 -Gensddiscu~nbn 168

capabilities of mere observation Quantitative gait analysis is the only means

currently available to me- accurate three-dimensional measurement of human

activities in daily living. This fact has been the source of documenting gait

asymmetry in tams of the functional task of lower extremities during waking.

Regarding this finding, from now 0x1, we should deal with the consequence of

these ideas in fuaher c l ica l evaluation and gait studies.

Standardized gait patterns allows the clinician or gait analyst to compare

pathologic gait patterns with a gold reference. When assuming similarity with

the contra-lateral S i b , gait analyses usually focused on the biomechanid

aspects of the right S i b only. However, when gait asymmetry is considered, at

leas two different types of gait patterns must be sen into account to describe

able-bodied gait references.

Clinician and gait analyst interests deal with high accuncy and precise

data However, gait symmetry is still inferred because of simplicity or

unavailability of advance technology. Having accurate and precise results is

directly related to advance technology that normally is too expensive. Moreover,

the gait measurement and evaluation system in clinical usage requires easily

available measurement and data processing (Yamamoto et al. 1983).

5.1.2- Importance of gait parameters identification

on asymmetry

Although it is important to choose parameters that are more relevant, each

gait parameter has its particular i n f o d o n Therefore, gait parameter selection

and analysis are insufiicient to completely describe individual data. Nonetheless,

this approach can be used to provide a global picture of able-bodied gait

The gait analyst should carellly consider the choice of gait parameters to

exclude redundant parameters. In this study, ten t e n p d gait parameters such as

speed. cadence, etc., as well as forty-four peak mechanical muscle powers and its

associated energy calculated at the hips, the knees, and ankles were analyzed.

The first and most important step was to select the most informative and

meaningful parameters among this relatively large number of parameters.

Identifying the parameters can be considered as characterizing the gait

phenomenon, which has been investigated as a main objective in gait studies

(Sadeghi et al. 1997). In general, the main purpose of gait identification is to

determine the most important and informative feature of the gait pameters.

In this study, temporal, mechanical muscle power and their corresponding

mechanical energies for both limbs am identified using the Principal

Component Analysis method. For the right limb, most of the identified

panmeters were associated with the hip, and were mainly in the sagittal plane in

genmting phases. These parameters were mostly concentrated during push-off.

While, for the left l i b , most of its activities were associated with the knee, and

were spread throughout the stance phase. Furthennore, they were related to the

fiuntal plane and absorbing which mostly is responsible in controlliig body

weight transfer during natural walking. These results were leading us to define

functional asymmeay in gait where one leg is mostly responsible for fonvard

progression while the other is controlling the lower l i b .

Many at[empts have been done in biomechanic studies to link the result of

asymmetry finding in gait with other sciences, but most of them occurred,

incidentally. Limb dominance as one of the well-known subjects was waluated

mostly in motor control sciences (Peter 1980). Recently, limb dominance has

been waluated in gait symmetry studies (Hamil et al. 1984.. Ounpuu and Winter

1989).

Most of the studies that examined the laterality characterized one limb in

terms of stability (support or control l i b ) and other mobility or forward

progression tasks. Therefore, it is reasonable to find out the relationship between

gait asymmetry and lateral dominance. Such a l i also could be seen between

other fields of sciences such as neurology and neuroscience and so on. In short,

relatively complete interpretation of gait asymmetry is highly related to different

areas of human sciences.

Gait asymmetry has been well documented (Sadeghi et al. 1997..

Hirowaka et al. 1989). however, little is known about propulsion and control task

performed by each l i b and how these are managed between lower limbs (Olney

et al, 1995, Hirokawa, 1989.. Lasko et al. 1990.. Andrew et al. 1996). The third

part of this study focused on how muscle power generation and absorption

activities were thought to be inter-Sib related. The study has shown that limb

Chapter 5 -General dirnrrrion 171

propulsion is mainly associated with the interaction between muscle power

generation bursts developed throughout the stance phase, while control is mainly

achieved by the contm-lateral Sib's muscle power absorption bursts. Inter-Sib

interaaion further emphas i i the functional relationship between forward

progression and control tasks developed by each limb and highlights the

importance of the hn ta l and transverse plane actions during gait.

5.13. Implication of asymmetry on gait analysis

Gait studies' results have been applicable in clinics as a diagnostic tool

to recognize normality h m abnormality, or selecting or evaluating effects of

surgery, physiotherapy or rehabilitation, and to design artificial limbs.

Standardizing gait patterns will be useful to evaluate and compare able-

bodied subjects or patients to a standard while gait parameter identification are

important for classification

Similarities between right and left lower limbs were inferred for

simplicity's sake (Gunderson et al. 1989) and numerous able-bodied gait

studies have relied on unilateral data (Apkarian et al. 1989.. Kadaba et al.

1989.. Eng and Winter 1995.. Vaughan et al. 1992). Therefore with respect to

this m p t i o n , clinicians for diagnoses and designers of artificial limbs do not

have any problem, since they can evaluate one S i b and then they can extend

their results to both limbs. But, to accept functional asymmetry, which has

Chapter 5 -General dirausion I 72

been documented by Sadeghi et al. (1997). and Hirokawa (1989) would change

the orientation of gait evaluation In this regard, the clinician needs to spend

more time in collecting and analyzing the data, since he or she could not deal

just with the results of evaluating one limb. They also need to provide a tool to

clarify the different mmevlings between the lower extremities' tasks and

abnormality. In other words, the fm step for the investigator and the clinician

should be to recognize the natural differences, which are related to forward

progession and control functional disabilities.

Gait asymmehy results are also very important to the artificial limb

designer that has to take different functional behaviors of lower extremities into

consideration. Furthermore, in the robotics field, robot programmers and

designers also need to take into account the control and forward progression

tasks when dealing with lower limbs of the robot Moreover, in research, to

compare lower extremities' parameters when both side data are not

simultaneously collected will not be appropriate. In other words, it will not be

acceptable to study and analyze one lower limb and then extend the results for

both limbs.

5.2. Limitations

There were a number of theoretical and methodological Sitations used in

this study, which are explain-d briefly.

The intent of any measurement is to capture the hue nature of an

observable phenomenon and translate it into nlrmbcrs All researchers know the

success of this translation is often fiaught with difficulties. Increasing the

reliability of the measurement as the central and defining features of systematic

observation is one of the most impoItant parts of any investigation This could be

achieved by carefully thinking in advance about the sources of m r in a potential

application

The human body cannot be viewed simply h r n a biomechanic standpoint

(McClay 1995). Movement occurs as a result of the integration of biomechanic,

neuro-physiology, or motor control systems working in concert- Furthermore,

simulations of walking have been driven by joint moments, muscle-lie forces or

in some cases, by gravity as the only force acting on the limbs. As muscle models

are developed and means of estimating their parameters become better established,

the use of muscle-like actuators will liely become more common in mathematical

gait models and other activities @amour 1995).

Muscle is not a pure force generator, its force depends on activation length

and velocity. Using muscle-lie actuators rather than pure force or moment

generators gives a more realistic response of the mechanical model. However, the

utility of a model depends on how well it represents gait features. Increasing the

number of degrees of freedom to depict multiple movements at each joinL is one

of the advantages included in the model used for this study.

Targeting a force plate during a gait assgsment does not significantly

UIIIpfer 5 -General discussion 174

affect the gmmd reaction forces (Grabiia et aL, 1995), but awareness on the part

of subject to take consecutive steps on each force plate during data collection may

have had an influence. The subjects always stepped on the £kt platform with

their right foot This had the advantage of having the largest number of trials for

that single condition but at the cost of increasing the chances of gait asymmetry.

Our subjects were evduated with their yms crossed over their chest, to

avoid occlusion of the pelvis and hip markers. This may have influenced our

results, since asymmetrical am? action has the potential to compensate for

asymmetries elsewhere in the body (Hinrichs, 1992). Furthermore, the relative

dsplacements of the markers due to soft tissue motion were not corrected by a

solidification process (Chm et al., 1995). The mechanical energies were also

calculated at each joint and for each plane iium the respective muscle powers.

although powers and energies are scalar terms. Nonetheless, this method was used

by Eng and Winter (1995). as well as Mad et al. (1996), to describe abl&odied

gait, and Loizeau et al. (1995) applied it to study patients fitted with total hip

prostheses.

Capability of assessing the simultaneous, bilateral three dimensional gait

da!a allows us to better understand the nature of gait Althou& ground reaction

forces and muscle moments are useful parametas to describe human locomotion

(Herzog et al. 1989) and to quantify gait disorder, mechanical muscle powers and

their associated energy provide a good indication of one's ability to control and

propel the lower limb. Recently, three dimensional muscle power data have been

Chanter 5 -General disausion 175

used to describe normal (Allard et al. 1996, 0unpr;u et al. 1991 and Eng and

Wmter, 1995) and pathological gait (Allard et al. 1995., Czernieclci et al. 1991

and L o ' i u et al. 1995). Muscle power data has been recognized as more

convenient pmmeters since they combine both kinematic and kinetic

information

The contribution of the trunk movement on the able-bodied and

pathological gait has been recognized for some time (Sunders et al. 1953.. Stokes

et al. 1989.. Kreb et al. 1992). Most investigations of spinal kinematics during

walking have considered either the entire trunk as a single segment or only the

lumbar spine. Examining able-bodied and pathological gaits with and without

fixing or crossing the hand on the chest as well as studying the influence of trunk

movement in their walking m e g y would be interesting for further analysis in

gait Covering the force plate, or using a larger size of force plate should wlve the

awareness of the subject about the location of the force plate. However, different

strategies for stepping on the force plates are also an interesting subject for

investigation

In the present study muscle powers and thcir associated energy developed

at the hips. knees and ankles as well as the temporal gait parameters have been

used to characterize able-bodied gait To our knowledge, there have been only a

few studies that dealt with simultaneous bilateral ~ e n s i o n a l gait analysis.

Moreover, availability of a h n c e d equipment and software allowed us to

document and quantify objectively able-bodied gait in collecting and processing

h e data It also provided an opportunity to use advanced statistical methods to

analyze the data in a reliable and accurate manna.

5.3. Retrospective analysis and comments for

further studies

There are some technical and theoretical points that are important to take

into account for any further gait studies and particularly for those interested in

investigating functional tasks of the lower extmnities.

Spatio-temporal and kinetics parameters should be analyzed individually

when using any type of classification such as Principal Component Analysis,

Canonical Correlation Analysis or Cluster Analysis methods. This led the

investigator to have better explanations as to the role of different types of

panmeters in gait However, the result of combining those types of parameters

during the identification procedure. showed the complex nature of human

locomotion as reflected by some parameters such as speed and step length. This

finding can be ccnsidered as another reason in accepting the ideas of high

dependency of gait analysis on some temporal p-eters such as speed (Olney et

al. 1994).

Gait is naturally described as a cyclic phenomenon Locomotion can be

expressed in terms of time functions, location or both having curve data

(continuos). They occur at the point the event is obsaved and are not the same

!?om one mad to another. More precisely, the main objective of continuous

data analysis is to study the variation in samples of functions. This would be a

major reason which invatigatoa should emphasize more than ever in the

analysis of the gait data as curve, instead of focusing in analyjing just some

instants of the curvature data (Eng and Wmter 1995, Allard et aL 1996).

Few shldies dealt with gait as continuous data (Lasssel et al. 1991..

Loslever et al. 1994.. Wooten et al. 1990, Davis and Vaughan 1993.. Deluzio

1997). To determine the common co-activity patterns of three-dimensional gait

data curve or evaluating gait asymmetry when the data arc curves would be

interesting and critical. Moreover, to use the data curve to characterize the

normal gait and to obtain some typical patterns to compare pathological gait

patterns is clinically important and might be clinically relevant

To analyze the data in a more reliable way, experimental protocols should

lead us to collect data as n d l y as possible. Crossing the hand on the chest

during the walking performance or the awareness of the subject of the location of

the force plates are limitations of the present study.

The determination of muscle and joint forces is one of the main subjects in

biomechanics. This leads to a better understanding of the muscle activity in which

generation and absorption occur during gait Evaluating functional asymmetry

and relationship assumptions based on activities' muscle moments calculated at

the hips, the knees and the ankles in three dimension for both continuous and peak

values data also is recommended.

Decomposing the variables into three dimensions and getting the hip, knee

and ankle data independent of each other is one advantage of the availability of the

advanced technology. However, it will be useful to find out a way to have the

resultant data and study the interaction Ween those paramems in each instance

of the gait cycle as welL To our knowledge, there are a few studies which have

done so (Winter et al. 1995). More studies in this regard are recommended.

Laterality is an interesting subject to evaluate in gait Few studies have

considered it (Ounpuu 1989.. Hannah i9S4). There is not enough evidence to

show the influence of laterality on control and forward progression tasks. In the

present study, right-handed subjects participated. Evaluation of the left handed

subjects with the same objectives that we have examined in this study would be

interesting to obtain the influence of laterality on lower extremities tasks.

There h v e been some few studies on able-bodied and pathological

women's gait ( M m y et al. 1970., F i e y et al. 1969). These were limited to the

description of the spatio-temporal and hematic parameters. In general, many

common unanswered questions remained for both men and women's gait

However, in order to detetmine the iduence of the gender on the gait,

investigation would be performed based on women gait data

Most of the pathological gait studies were done on individual subjects

descriptive analysis (Whittle 1991). The comparison of gait characteristics

among of patients would be difficult, since the gait pattern differ h m one panem

to another (Yamamoto et aL 1983). But gait evaluation using advanced statistical

methods like Principal Component Analysis allows us to organize various patients

into the same scale and make the comparison easier. Thaefoq it will be

worthwhile if gait standardintio~, identification, and functional asymmetry as

well as functional relationships were evaluated using advanced statistical methods.

Nowadays researchen are confiunted with extensive amounts of gait data

gathemi by sophisticated and advanced instnunents. A complete description of

human gait requires linear and temporal gait parameten as well as waveform

information such as limb rotations, forces, and moments at the joints and phasic

activity of muscles. This results in a large number of interactive parameters,

making interpretation of gait data extremely difficult

Different methods and approaches have been used to simplify this

problem. They have been also used to characterize normal and pathological gait

by one or several typical patterns of relevant gait parameten (Olney et al. 1994..

Mah et al. 1994.. Loslever et aL 1994., Holaeiter and Kohle 1993., Sadeghi et al.

1997). These advanced statistical methods are opening new and promising

horizons towards characterization of normal and pathological gait Further studies

using such advanced statistical methods are strongly recommended.

VI - Conclusion

Our results h-ing further evidence to support the idea of a functional gait

asymmetry. According to this finding, not only significant differences can be

observed between the identified temporal and kinetics gait parameters calculated

at the hips, knees and ankles during walking, but also those differences are

intapretable in tams of propulsion and control tasks of the lower extremities.

Furthermore, identifying the temporal and kinetics gait parameters using the

Rincipal Component Analysis provided a condition to identify as well as to

classify th.:: gait parameters. The l i b , which had a propulsion function, was

chmtaized by a strong H3S bursf and most of the parameters identified by the

PCA were associated with the hip and bee. These were concentrated during the

push-off period. There was a secondary support function, which occurred during,

mid-stance. For the limb having a supporting function, most of its activities were

associated with the knee, and these were spread throughout the stance phase.

None of them was associated with propulsion.

A high relationship and coordination was found between the forward

progression and control gait parameters. Visual symmetry in gait is the outcome

of the interaction and high correlation between the gait parameters in each and

both lower extrrmitics. This study has demonstrated thy propulsion of the lower

limb was asso&ed with the intaaction between muscle power bursts developed

throughout the stance phasc while conno1 was achieved by the contn-lateral limb.

For the right limb, propulsion was an activity initiated by the hip shortly after

heel-strike and maintained throughout the stance phase. Our results do not support

the idas that the ankle is a major conmbutor to fonv;ad progression Control was

the main task of the left limb as evidenced by the power absorption bums. The

left limb power genaations were generally secondary to control activities or

possibly to corrat for the right limb propulsion Inter-limb interaction further

emphasized the functional relationship between fonvard p r o p s i o n and control

tasks developed by each limb and highlighted the importance of the frontal and

transverse plane action during gait.

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