Classification of multivariate gait EMG patterns in cerebral palsy

Classification of multivariate gait EMG patterns in cerebral palsy

266 Absiract Session I Goit & Posture Two ACROSS-LABORATORY SURFACE LABORATORIES RELIABILITY OF TIMING EMG ACTIVITY OBTAINED USING STANDARDIZE...

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266

Absiract

Session

I Goit & Posture

Two

ACROSS-LABORATORY SURFACE LABORATORIES

RELIABILITY

OF TIMING

EMG ACTIVITY OBTAINED USING STANDARDIZED

Roe&n&

PARAMETERS

DURING GAIT MEASUREMENT

OF

IN THREE TECHNIQUE

Kleissen RFM, Litjens MCA, Batcn CTM, Burke J, Harlaar I*, Hof AL**, Zilvold G. Research and Development, Enschede, the Netherlands

* Rehabilitation Department, Free University Hospital Amsterdam ** Rehabilitation Department, Academic Hospital Groningen

INTRODUCTION

Various xmrccs de&be the use of electromyography in planning of surgical intervention in cerebral palsy. However, because such practice is developed locally, it is unknown if, and to what extend EMG recordings are comparable between individual laboratories. As an exploration of the practical communicability of EMG records obtained in gait analysis, the purpose of this study is to investigate the consistence of surface EMG recordings obtained in different laboratories from gait using standardwed mcasurcmcnt technique.

6 (1997)

263-280

oped a new method of multishaonel EMG quantif~ation based on principal component (PC) analysis to characterize normal and pathological EMG patterns, to identify correlations with clinical scores, and to evaluate the benefits of clinical interventions. Methods Surface EMG recordings were made from 8 kg muscles on either side while children (nine controls, eight cerebral palsy patients; 4 to 6 years) walked with minimal assistance at a c&mfortabk s&ed along a walkway. The EMGs were diititized at 500/s. low oass filtered (12.5 Hz). rectified and normalized within t&h step cycle. ~&nci&&i component (PC) analysis was applied for data reduction sod identification of consistent pattems of EMG activity across the 8 EMG profiles. The method is ao extension of a technique of PC-based synergy analysis that has previously been used successfully for quantification of multivariate kinematic gait pauerns (I). PCs are cyclic waveforms calculated as optimally weighted sums of r&tied smoothed EMG signals. mey are characterized by the set of 8 weight factors, which in turn describe the relative conbibution of each EMG signal to a given PC. PCs describe synergies and allow significant data reduction. Thus, istier quantitative charactehzation of 8. channel EMG patterns can be restricted to the analysis of a smaller number of signals: two. if 60-6596 of total signal variance is to be considered. three, for 70-75% of total sienal. four. for 80-85% of total sienal. The variabilitv of these synergies within and ‘be&n groups was deten&ed from PC phase plots (PC2 vs. PCI). The degree of abnormality of cerebral palsy patterns was further characterized by calculating the magnitude of the normal EMG synergies that could be identified in pathological patterns or by estimating the magnitude of the total signal that was attributed to pathology. Results

METHODOLOGY

Gait labs of tbrce clinical institutes participated in this study. Ten male and ten female normals walked at comfortable walking speed in all three labs. Each lab was equipped with functionally equivalent instrumentation [ I 1. Ensemble averaged surface EMG profiles were recorded over more than 20 gait cycles for rectus fcmoris, scmitcodinosos, tibialis anterior and gastrocnemios medialis muscles using a written elstrodc placement protocol following Winter and Yack [ 2 ]. Bipolar electrodes were placed by local staff of each lab; there ulas no commtmication between the staff members of the three labs. For each EMG profile the instant of onset (TO) , peak (TP) and cessation (TC) of muscle activity was determined fully automatically using prescribed algorithms. For each subject and muscle range of TO, TP and TC ( exprcsacd as a percentage of normalized gait cycle duration ) across the three laboratories was determined. Median and mean deviation from the median were used to summarize this obscxvcd ranges for all 20 subtccts.

Queotitstive analysis of muscle synergies showed that for comml children the EMG patterns were mostly consistent between. within and between sttbiecu. They could therefore be effectively chamcwized by common PC wei-ght facto& (permitting analysis in a cc&on weight spscc) and by average. PC waveforms. In cerebral ttals~. EMG oaturns reveakd sieniticant variabilitv of the muscle synergies du&g~&ing.‘bub within and b&eeo subjects. 1; order to characterize the range of patterns obsetved, single gait cycle psttems and individual a-wage patteras were compared with the average normal pattern (using the cornmix space of PC weight factors). Individual cerebral palsy activity patterns were examined for remnants of this normal EMG activity. Results iticate that padents utilize patterns of musek activity ranging from: i) rudimentawnonnal. where elements of the normal oattern were clearly identified in tbi pathological muscle activity profiles; to’b) extremely patb&ical, where practically no remnants of the normal muscle activity pattern could be detected. Preliminary analysis revealed promising correlations with clinical indices. Discussion

RESULTS

TO, TP and TC derived from the EMG pmfiler for each subject and a given muscle is fairly consistent across the laboratories. We see considerable intersubject differences, but the repeatability within one subject is only a few percent of the nonoalizcd gait cycle duration. Best across laboratory repeatability was found for TC of tibialis anterior ( median for range m TC is 1.7 %, mean deviation from median is 0.2 % ). Worst repeatability was found for TC of sctnitendinosus ( median for range m TC is 6.0 %, mean deviation from median is 5.7 % ).

The functional interpretation of PC waveforms is not straightforward. Judging from the weight factor profiles it is evident that individual PCs do not reflect simple anatomical (e.g. flexor/extensor) synergies. Instead they atwear to represent &ctionaJ synergks of anatomically h&ogenous mu&e’ ‘groups acting across different joints that are activated in phase. Attempts have been initiated to determine whether useful kinematic equivalents of EMG PCs can bc identified. wine comouter simulations of human eait (2). Q&i&e m’&wres of EMG pattern abn&al&y appeared to he cow+ ated with clinical severity of gait impairment. This suggests that with a larger samok of oatients auantitative criteria for statistical classification of oatholog&l gait ‘EMG pat&s can be established. References

DISCUSSION It appears fmm these data that standardized EMG recording allows wnsistent measurements of shape of an EMG profile and instant of peak activity across different laboratories. This is an important property if cxcbaoge of EMG data across laboratoris, for instance for teleconsultation purposes is considered. Fwthcrmorc. it justifies standardization efforts related to EMG measurcrncnt technique. REFERENCES

I. 2.

Supported Canada.

M. Hulliger.

OF MULTIVARIATE CEREBRAL A. Wojciechowski.

G. Bishop Dept. of Clinical sod Alberta

GAIT PALSY

by the Alberta

A thmdimemional

I. Kleissen RFM et al., Med Biol Eng Comput 27: 291-297, 1989. 2. Winter DA, Yack HI, Elcctroenccph Clin Neural 67: 402 - 41 I, 1987

CLASSIFWATION

Msh, CD.. Hulliger, M., Let, R.G. & O’Callaghan, I (1994). Quantirarive analysis of human movement synergies: constructive pattern analysis for gait. Journal of Moror Behavior 26. 83-102. Or&en, K.G.M., van den Bogen. A.J. & Hulliger, M. (I9Y6). Direct dynamics simulation of FES-assisted locomotion. In Proceedings of rhe Inrernalional Symposium on Smart Srrucrures and Morerials. Vol. 2718. 481.491.

EMG

H.Z. Darwisb’, M. McNeil, & J.P.A. Foweraker

PA’ll’FaRNS

IN

A. Dypvik,

Neurosciences. Univ. of Calgary, Alberta, Can&a T2N 4NI Children’s Hospital’, Calgary, Alberta, Canada TZT 5C7

Introduction Qmmtimtive classification of multivariate (global) EM0 pattems during gait is a major challenge. given the pronounced variability between and within subjects and rhe partial redundancy between EMG profiles of different (synergistic) muscles. This is especially tme for pathological EMG io motor disorders. Sy8temadc and statistical analysis of such EMG patterns is badly needed for gair evaloarion in diagnostics and intervention outcome studies. We have devel-

malyais

Children’s

Hospital

Foundation,

AHFMR

and NCE

of the @mma ratlion force vcclor p@tWns in normal and paIhofogical gait

Saunders (1953) suggested that gait is a method of traiaslation of the ccntrc of gravity through space akmg a pathway rcqoiriog tbc least expenditure of eocrgy. The [email protected]~ of tbc ceatrc of gravity gives rise to varying forces acting throu8h tbc mpporting limb which CM be assess& by anaJ@~g tbc ground reaction force vector with a force plate This is ncmally done in the sagittaJ plaae. Wafking, however, is a thrse-dbnensional activity and it k thsrefore reason&k thst attention should he pnid to the ground m&ion force w,or in all tbre dbncnsiorts This studv was set up to look at the nomtd pattern of the reaction force vector in Ihe sagittal. coronal sod traoswse ptaaea in a g&p of nonoal individuals and in a select group of paderas with hcmiplegia sod diplegia. ‘uek?d

Ape-matched normal, hemiplegic and diikgic patients MPX30 motion analysis system sad s Kiukx force pIate. as.scssmsnt of both lower limbs sod tk pelvis in all tti then transferred to a three-dimensional pwgram where it reaction force vector in any one dimension or in the three

were assessed using tb? CodaThis system allows simabamoos plsozs. The data collected wss was possible to view the ground dimensions combined.