Assessing altered motor unit recruitment patterns in paretic muscles of stroke survivors using surface electromyography

Xiaogang Hu, Aneesha K. Suresh, William Z. Rymer, Nina L. Suresh

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

Objective. The advancement of surface electromyogram (sEMG) recording and signal processing techniques has allowed us to characterize the recruitment properties of a substantial population of motor units (MUs) non-invasively. Here we seek to determine whether MU recruitment properties are modified in paretic muscles of hemispheric stroke survivors. Approach. Using an advanced EMG sensor array, we recorded sEMG during isometric contractions of the first dorsal interosseous muscle over a range of contraction levels, from 20% to 60% of maximum, in both paretic and contralateral muscles of stroke survivors. Using MU decomposition techniques, MU action potential amplitudes and recruitment thresholds were derived for simultaneously activated MUs in each isometric contraction. Main results. Our results show a significant disruption of recruitment organization in paretic muscles, in that the size principle describing recruitment rank order was materially distorted. MUs were recruited over a very narrow force range with increasing force output, generating a strong clustering effect, when referenced to recruitment force magnitude. Such disturbances in MU properties also correlated well with the impairment of voluntary force generation. Significance. Our findings provide direct evidence regarding MU recruitment modifications in paretic muscles of stroke survivors, and suggest that these modifications may contribute to weakness for voluntary contractions.

Original languageEnglish (US)
Article number066001
JournalJournal of Neural Engineering
Volume12
Issue number6
DOIs
StatePublished - 2015

Keywords

  • Chronic stroke
  • Motor unit
  • Muscle weakness
  • Recruitment threshold
  • Surface electromyogram

ASJC Scopus subject areas

  • Biomedical Engineering
  • Cellular and Molecular Neuroscience

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