Quantifying the Peak Amplitude Distributions of Electromyogram in Bicep Brachii muscle after Stroke

Taimoor Afzal, Andrew Lai, Xiaogang Hu, William Z. Rymer*, Nina L. Suresh

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The objective of this study was to quantify the differences in surface electromyogram (EMG) signal characteristics between affected and contralateral arm muscles of hemispheric stroke survivors. EMG signals were recorded from the biceps brachii muscles using single differential electrodes. Four chronic stroke subjects performed isometric elbow flexions at sub-maximal voluntary contraction levels on both the affected and contralateral limbs. The force generated on the contralateral side was matched to the force generated on the affected side. We observed different types of EMG activation on the affected side compared to the contralateral side.Specifically, two subjects showed lower RMS EMG activity on the affected side whereas two subjects showed greater EMG activity on the affected side compared to the contralateral side. Analysis of the peak amplitudes of the EMG activity showed greater number of peaks in the EMG on affected side compared to the contralateral side in all subjects. The histogram of the peak amplitudes showed greater number of smaller peak amplitudes in subjects with lower EMG activity on the affected side suggesting a reliance on smaller motor units. Our combined EMG signal analysis techniques on one set of recorded signals provides insight regarding potential mechanisms of weakness.Clinical Relevance - Decoding neural information from surface EMG signals without decomposition into individual motor units could provide clinicians with quick insight about disease progress and potential treatment.

Original languageEnglish (US)
Title of host publication42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationEnabling Innovative Technologies for Global Healthcare, EMBC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3739-3742
Number of pages4
ISBN (Electronic)9781728119908
DOIs
StatePublished - Jul 2020
Event42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020 - Montreal, Canada
Duration: Jul 20 2020Jul 24 2020

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2020-July
ISSN (Print)1557-170X

Conference

Conference42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020
CountryCanada
CityMontreal
Period7/20/207/24/20

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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