Quantification of muscle fatigue using surface electromyography for isometric handgrip task

We proposed a method to quantitatively estimate the degree of muscle fatigue by constructing a fatigue index, which represents the relationship between the force loss and handgrip work. This fatigue model allows the estimation of force loss non-intrusively using SEMG signal. Eight male subjects volu...

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Main Author: Jawatankuasa Kerja PSM UTeM
Other Authors: Yewguan, Soo
Format: Journal
Published: Journal of Telecommunication, Electronic and Computer Engineering, Universiti Teknikal Malaysia Melaka 2017
Subjects:
Online Access:http://www.myjurnal.my/public/article-view.php?id=114627
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spelling oai:www.myjurnal.my:1146272018-09-20T00:00:00Z Quantification of muscle fatigue using surface electromyography for isometric handgrip task Jawatankuasa Kerja PSM UTeM Engineering We proposed a method to quantitatively estimate the degree of muscle fatigue by constructing a fatigue index, which represents the relationship between the force loss and handgrip work. This fatigue model allows the estimation of force loss non-intrusively using SEMG signal. Eight male subjects volunteered in this study to perform a series of isometric handgrip tasks at three different contraction levels. Handgrip work was estimated from SEMG signal, which was then used as the independent parameter for the fatigue index to estimate the force loss. The evaluation was performed by comparing the force loss that was estimated using the proposed fatigue index and the one measured from dynamometer. The average error of the estimated muscle fatigue using the proposed method was less than 10% MVC. Journal of Telecommunication, Electronic and Computer Engineering, Universiti Teknikal Malaysia Melaka Yewguan, Soo 2017-00-00 Journal application/pdf 114627 www.myjurnal.my/filebank/published_article/63488JTEC_31.pdf www.myjurnal.my/public/article-view.php?id=114627
repository_type Digital Repository
institution_category Local Institution
institution MyJournal
building MyJournal Repository
collection Online Access
topic Engineering
spellingShingle Engineering
Jawatankuasa Kerja PSM UTeM
Quantification of muscle fatigue using surface electromyography for isometric handgrip task
description We proposed a method to quantitatively estimate the degree of muscle fatigue by constructing a fatigue index, which represents the relationship between the force loss and handgrip work. This fatigue model allows the estimation of force loss non-intrusively using SEMG signal. Eight male subjects volunteered in this study to perform a series of isometric handgrip tasks at three different contraction levels. Handgrip work was estimated from SEMG signal, which was then used as the independent parameter for the fatigue index to estimate the force loss. The evaluation was performed by comparing the force loss that was estimated using the proposed fatigue index and the one measured from dynamometer. The average error of the estimated muscle fatigue using the proposed method was less than 10% MVC.
author2 Yewguan, Soo
author_facet Yewguan, Soo
Jawatankuasa Kerja PSM UTeM
format Journal
author Jawatankuasa Kerja PSM UTeM
author_sort Jawatankuasa Kerja PSM UTeM
title Quantification of muscle fatigue using surface electromyography for isometric handgrip task
title_short Quantification of muscle fatigue using surface electromyography for isometric handgrip task
title_full Quantification of muscle fatigue using surface electromyography for isometric handgrip task
title_fullStr Quantification of muscle fatigue using surface electromyography for isometric handgrip task
title_full_unstemmed Quantification of muscle fatigue using surface electromyography for isometric handgrip task
title_sort quantification of muscle fatigue using surface electromyography for isometric handgrip task
publisher Journal of Telecommunication, Electronic and Computer Engineering, Universiti Teknikal Malaysia Melaka
publishDate 2017
url http://www.myjurnal.my/public/article-view.php?id=114627
first_indexed 2018-09-20T16:29:08Z
last_indexed 2018-09-20T16:29:08Z
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