The effect of myoelectric computer interface training on arm kinematics and function after stroke

Goran Tomic, Emily M. Mugler, Aparna Singh, Jonathan Gaide, Saad Hameed, Murad Alqadi, Elizabeth Robinson, Marc W. Slutzky

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

Abstract

Abnormal co-activation patterns of arm muscles is a substantial cause of impaired arm function after stroke. We designed a myoelectric computer interface (MCI) training paradigm to help stroke survivors reduce this abnormal coactivation. Here, we evaluated the effects of MCI training on function and arm kinematics in 32 chronic stroke survivors. We compared the effects of training duration and isometric vs. movement-based training conditions in 3 different groups. All groups reduced abnormal co-activation in targeted muscles, and showed reduced arm impairment after 6 weeks of training. They also showed improvements in arm kinematics as well as functional scores. Moreover, the gains persisted, though most were reduced, at one month after training stopped. These results suggest that MCI training holds promise to improve arm function after stroke.

Original languageEnglish (US)
Title of host publication40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2479-2482
Number of pages4
ISBN (Electronic)9781538636466
DOIs
StatePublished - Oct 26 2018
Event40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 - Honolulu, United States
Duration: Jul 18 2018Jul 21 2018

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2018-July
ISSN (Print)1557-170X

Other

Other40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
Country/TerritoryUnited States
CityHonolulu
Period7/18/187/21/18

ASJC Scopus subject areas

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

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