Features Extraction of Electromyography Signals in Time Domain on Biceps Brachii Muscle

Electromyography (EMG) is widely used in various fields to investigate the muscular activities. Since EMG signals contain a wealth of information about muscle functions, there are many approaches in analyzing the EMG signals. It is important to know the features that can be extracting from the EMG s...

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Main Author: W. Daud, W. M. Bukhari
Format: Article
Language:English
Published: IACSIT Press 2013
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Online Access:http://eprints.utem.edu.my/id/eprint/10154/1/journal_ijmo_scan.pdf
http://eprints.utem.edu.my/id/eprint/10154/
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Institution: Universiti Teknikal Malaysia Melaka
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spelling my.utem.eprints.101542015-05-28T04:09:25Z http://eprints.utem.edu.my/id/eprint/10154/ Features Extraction of Electromyography Signals in Time Domain on Biceps Brachii Muscle W. Daud, W. M. Bukhari T Technology (General) Electromyography (EMG) is widely used in various fields to investigate the muscular activities. Since EMG signals contain a wealth of information about muscle functions, there are many approaches in analyzing the EMG signals. It is important to know the features that can be extracting from the EMG signal. The ideal feature is important for the achievement in EMG analysis. Hence, the objective of this paper is to evaluate the features extraction of time domain from the EMG signal. The experiment was setup according to surface electromyography for noninvasive assessment of muscle (SENIAM). The recorded data was analyzed in time domain to get the features. Based on the analysis, three features have been considered based on statistical features. The features was then been evaluate by getting the percentage error of each feature. The less percentage error determines the ideal feature. The results shows that the extracted features of the EMG signals in time domain can be implement in signal classification. These findings could be integrated to design a signal classification based on the features extraction. IACSIT Press 2013-12 Article PeerReviewed application/pdf en http://eprints.utem.edu.my/id/eprint/10154/1/journal_ijmo_scan.pdf W. Daud, W. M. Bukhari (2013) Features Extraction of Electromyography Signals in Time Domain on Biceps Brachii Muscle. International Journal of Modelling and Optimization (IJMO), 3 (6). pp. 515-519. ISSN 2010-3697
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
topic T Technology (General)
spellingShingle T Technology (General)
W. Daud, W. M. Bukhari
Features Extraction of Electromyography Signals in Time Domain on Biceps Brachii Muscle
description Electromyography (EMG) is widely used in various fields to investigate the muscular activities. Since EMG signals contain a wealth of information about muscle functions, there are many approaches in analyzing the EMG signals. It is important to know the features that can be extracting from the EMG signal. The ideal feature is important for the achievement in EMG analysis. Hence, the objective of this paper is to evaluate the features extraction of time domain from the EMG signal. The experiment was setup according to surface electromyography for noninvasive assessment of muscle (SENIAM). The recorded data was analyzed in time domain to get the features. Based on the analysis, three features have been considered based on statistical features. The features was then been evaluate by getting the percentage error of each feature. The less percentage error determines the ideal feature. The results shows that the extracted features of the EMG signals in time domain can be implement in signal classification. These findings could be integrated to design a signal classification based on the features extraction.
format Article
author W. Daud, W. M. Bukhari
author_facet W. Daud, W. M. Bukhari
author_sort W. Daud, W. M. Bukhari
title Features Extraction of Electromyography Signals in Time Domain on Biceps Brachii Muscle
title_short Features Extraction of Electromyography Signals in Time Domain on Biceps Brachii Muscle
title_full Features Extraction of Electromyography Signals in Time Domain on Biceps Brachii Muscle
title_fullStr Features Extraction of Electromyography Signals in Time Domain on Biceps Brachii Muscle
title_full_unstemmed Features Extraction of Electromyography Signals in Time Domain on Biceps Brachii Muscle
title_sort features extraction of electromyography signals in time domain on biceps brachii muscle
publisher IACSIT Press
publishDate 2013
url http://eprints.utem.edu.my/id/eprint/10154/1/journal_ijmo_scan.pdf
http://eprints.utem.edu.my/id/eprint/10154/
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