z-logo
Premium
Are leg electromyogram profiles symmetrical?
Author(s) -
Pierotti Stephen E.,
Brand Richard A.,
Gabel Ronald H.,
Pedersen Douglas R.,
Clarke William R.
Publication year - 1991
Publication title -
journal of orthopaedic research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.041
H-Index - 155
eISSN - 1554-527X
pISSN - 0736-0266
DOI - 10.1002/jor.1100090512
Subject(s) - abnormality , mathematics , normal population , symmetry (geometry) , population , electromyography , motor unit , similarity (geometry) , anatomy , degree (music) , leg muscle , pattern recognition (psychology) , statistics , physical medicine and rehabilitation , psychology , computer science , medicine , physics , artificial intelligence , geometry , acoustics , social psychology , environmental health , image (mathematics)
Abstract Electromyographic (EMG) patterns reflect function of the neuromuscular system. Abnormality of a given pattern may be established by comparison with that of the contralateral (presumably normal) limb if one ensures a difference beyond normal degrees of symmetry. We studied EMG patterns in six homologous knee muscles during freely selected, slow, and fast gaits in normal subjects. EMG signals were electronically conditioned to produce linear envelopes; envelopes from at least eight cycles from each subject at each speed were ensemble averaged. Grand ensemble averages for each muscle and speed were assembled from all subjects for right and left muscles. Transformed correlation coefficients ( r ′) and variance ratios established the degree of similarity. All muscles exhibited a fair degree of symmetry (mean r ′ = 0.797 − 0.953), but we saw exceptions. On rare occasion, muscles repeatedly exhibited monophasic signals on one side and biphasic on the other. With increasing speed, signals generally became more repeatable, but we occasionally saw monophasic patterns becoming biphasic or vice versa. Considerable caution is essential before presuming any given pattern is abnormal. To ensure that a given pattern is abnormal one could establish that the pattern lies outside some statistical limits for normal population pattern controlled for speed and outside statistical limits for normal symmetry. Alternatively, one could determine the level of statistical differences in EMG patterns associated with distinct differences in level of functional performance between normal subjects and patients.

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here