Co-contraction of antagonist muscles during knee extension against gravity: insights for functional electrical stimulation control design.

Cheryl L. Lynch, Dimitry Sayenko, Milos R. Popovic

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

11 Scopus citations

Abstract

Functional electrical stimulation (FES) involves electrically stimulating the neuromuscular system to generate skeletal muscle contractions in paralyzed muscles. Several new FES applications have been proposed that require closed-loop control systems. Co-contraction of antagonist muscle groups has been postulated as a promising approach for closed-loop control of FES systems. However, this control approach has not yet been used in practical FES applications, in part due to a lack of information concerning how able-bodied subjects use co-contraction of antagonist muscles during standard control tests such as unit step and sinusoidal responses. The purpose of this work is to elucidate how able-bodied individuals use co-contraction by analyzing the EMG activity of antagonist muscles during voluntary knee extension against gravity. The results clearly demonstrate that able-bodied subjects use a co-contraction strategy when executing standard control performance tests, and strengthen the argument for using a co-contraction strategy for closed-loop FES control algorithms. These data will inform the development of new and effective controllers for FES applications.

Original languageEnglish (US)
Title of host publication2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012
Pages1843-1846
Number of pages4
DOIs
StatePublished - 2012
Event34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 - San Diego, CA, United States
Duration: Aug 28 2012Sep 1 2012

Other

Other34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012
CountryUnited States
CitySan Diego, CA
Period8/28/129/1/12

ASJC Scopus subject areas

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

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