The Effects of EMG Based Fatigue-Controlled and Forced Exercise on Motor Function Recovery: A Pilot Study

Yuchen Xu, Kedi Xu, Hao Lyu, Stephanie Ng, Wai Sang Poon, Shaomin Zhang, Xiaoling Hu, Yongping Zheng

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Post-stroke physical training resulting in fatigue may affect motor rehabilitation. In this study, we compared the effects of fatigue-controlled and forced treadmill running on motor recovery based on a rat intracerebral hemorrhage (ICH) model. Twelve Sprague-Dawley rats with ICH received electromyography (EMG) electrodes implantation in the gastrocnemius muscle in the affected hindlimb. They were randomly distributed into three groups: control (n=4), forced exercise (n=4) and fatigue-controlled (n=4) groups. The training intensity in the fatigue-controlled exercise was monitored by calculating the real-time mean power frequency (MPF) of EMG. The training intervention started from forty-eight hours after ICH surgery. Modified neurological severity score was applied daily during the following 13-day intervention to evaluate motor recovery. The results showed that fatigue-controlled group achieved the best motor recovery compared with the other two (P < 0.05).

Original languageEnglish
Title of host publication9th International IEEE EMBS Conference on Neural Engineering, NER 2019
PublisherIEEE Computer Society
Pages25-28
Number of pages4
ISBN (Electronic)9781538679210
DOIs
Publication statusPublished - 16 May 2019
Event9th International IEEE EMBS Conference on Neural Engineering, NER 2019 - San Francisco, United States
Duration: 20 Mar 201923 Mar 2019

Publication series

NameInternational IEEE/EMBS Conference on Neural Engineering, NER
Volume2019-March
ISSN (Print)1948-3546
ISSN (Electronic)1948-3554

Conference

Conference9th International IEEE EMBS Conference on Neural Engineering, NER 2019
CountryUnited States
CitySan Francisco
Period20/03/1923/03/19

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering

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