Analysis of the biceps brachii muscle by varying the arm movement level and load resistance band

Biceps brachii muscle illness is one of the common physical disabilities that requires rehabilitation exercises in order to build up the strength of the muscle after surgery. It is also important to monitor the condition of the muscle during the rehabilitation exercise through electromyography (EMG)...

Full description

Saved in:
Bibliographic Details
Main Authors: Burhan, N., Kasno, M. A., Ghazali, R., Said, M. R., Abdullah, S. S., Jali, M. H.
Format: Article
Language:English
Published: Hindawi Limited 2017
Subjects:
Online Access:http://eprints.utm.my/id/eprint/74912/1/NuradebahBurhan_AnalysisoftheBicepsBrachiiMuscle.pdf
http://eprints.utm.my/id/eprint/74912/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030644690&doi=10.1155%2f2017%2f1631384&partnerID=40&md5=b6d4657e3053882e91b83078fa7f0328
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utm.74912
record_format eprints
spelling my.utm.749122018-03-22T10:57:49Z http://eprints.utm.my/id/eprint/74912/ Analysis of the biceps brachii muscle by varying the arm movement level and load resistance band Burhan, N. Kasno, M. A. Ghazali, R. Said, M. R. Abdullah, S. S. Jali, M. H. TK Electrical engineering. Electronics Nuclear engineering Biceps brachii muscle illness is one of the common physical disabilities that requires rehabilitation exercises in order to build up the strength of the muscle after surgery. It is also important to monitor the condition of the muscle during the rehabilitation exercise through electromyography (EMG) signals. The purpose of this study was to analyse and investigate the selection of the best mother wavelet (MWT) function and depth of the decomposition level in the wavelet denoising EMG signals through the discrete wavelet transform (DWT) method at each decomposition level. In this experimental work, six healthy subjects comprised of males and females (26 ± 3.0 years and BMI of 22 ± 2.0) were selected as a reference for persons with the illness. The experiment was conducted for three sets of resistance band loads, namely, 5 kg, 9 kg, and 16 kg, as a force during the biceps brachii muscle contraction. Each subject was required to perform three levels of the arm angle positions (30°, 90°, and 150°) for each set of resistance band load. The experimental results showed that the Daubechies5 (db5) was the most appropriate DWT method together with a 6-level decomposition with a soft heursure threshold for the biceps brachii EMG signal analysis. Hindawi Limited 2017 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/74912/1/NuradebahBurhan_AnalysisoftheBicepsBrachiiMuscle.pdf Burhan, N. and Kasno, M. A. and Ghazali, R. and Said, M. R. and Abdullah, S. S. and Jali, M. H. (2017) Analysis of the biceps brachii muscle by varying the arm movement level and load resistance band. Journal of Healthcare Engineering, 2017 . ISSN 2040-2295 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030644690&doi=10.1155%2f2017%2f1631384&partnerID=40&md5=b6d4657e3053882e91b83078fa7f0328
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Burhan, N.
Kasno, M. A.
Ghazali, R.
Said, M. R.
Abdullah, S. S.
Jali, M. H.
Analysis of the biceps brachii muscle by varying the arm movement level and load resistance band
description Biceps brachii muscle illness is one of the common physical disabilities that requires rehabilitation exercises in order to build up the strength of the muscle after surgery. It is also important to monitor the condition of the muscle during the rehabilitation exercise through electromyography (EMG) signals. The purpose of this study was to analyse and investigate the selection of the best mother wavelet (MWT) function and depth of the decomposition level in the wavelet denoising EMG signals through the discrete wavelet transform (DWT) method at each decomposition level. In this experimental work, six healthy subjects comprised of males and females (26 ± 3.0 years and BMI of 22 ± 2.0) were selected as a reference for persons with the illness. The experiment was conducted for three sets of resistance band loads, namely, 5 kg, 9 kg, and 16 kg, as a force during the biceps brachii muscle contraction. Each subject was required to perform three levels of the arm angle positions (30°, 90°, and 150°) for each set of resistance band load. The experimental results showed that the Daubechies5 (db5) was the most appropriate DWT method together with a 6-level decomposition with a soft heursure threshold for the biceps brachii EMG signal analysis.
format Article
author Burhan, N.
Kasno, M. A.
Ghazali, R.
Said, M. R.
Abdullah, S. S.
Jali, M. H.
author_facet Burhan, N.
Kasno, M. A.
Ghazali, R.
Said, M. R.
Abdullah, S. S.
Jali, M. H.
author_sort Burhan, N.
title Analysis of the biceps brachii muscle by varying the arm movement level and load resistance band
title_short Analysis of the biceps brachii muscle by varying the arm movement level and load resistance band
title_full Analysis of the biceps brachii muscle by varying the arm movement level and load resistance band
title_fullStr Analysis of the biceps brachii muscle by varying the arm movement level and load resistance band
title_full_unstemmed Analysis of the biceps brachii muscle by varying the arm movement level and load resistance band
title_sort analysis of the biceps brachii muscle by varying the arm movement level and load resistance band
publisher Hindawi Limited
publishDate 2017
url http://eprints.utm.my/id/eprint/74912/1/NuradebahBurhan_AnalysisoftheBicepsBrachiiMuscle.pdf
http://eprints.utm.my/id/eprint/74912/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030644690&doi=10.1155%2f2017%2f1631384&partnerID=40&md5=b6d4657e3053882e91b83078fa7f0328
_version_ 1643656969488171008
score 13.211869