Muscle fatigue estimation with twitch force derived from sEMG peaks

Youngjin Na, Hae Dong Lee, Jung Kim

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

1 Citation (Scopus)

Abstract

We propose a new method - twitch force - for estimation of the muscle behavior during voluntary contraction for assessing localized muscle fatigue. The proposed method uses the sEMG peaks as input and the measured force as output. The twitch force, which is a transfer function to generate force, was estimated during fatiguing contraction. We verified the estimated twitch force based on the measured results with electrical stimulation. The participants performed isometric little finger flexion until exhaustion. SEMG was recorded on the flexor digiti minimi brevis muscle for the proposed method and the electrical stimulation electrodes on the ulnar nerve induced involuntary contraction for reference. As the muscle fatigue level increased, the twitch peaks decreased in both methods. The proposed method can be widely used in the quantitative analysis of muscle fatigue during voluntary contraction.

Original languageEnglish
Title of host publication2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3492-3495
Number of pages4
ISBN (Electronic)9781424492718
DOIs
Publication statusPublished - 2015 Nov 4
Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy
Duration: 2015 Aug 252015 Aug 29

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2015-November
ISSN (Print)1557-170X

Other

Other37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
CountryItaly
CityMilan
Period15/8/2515/8/29

All Science Journal Classification (ASJC) codes

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

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