Electromyography Signals on Biceps Brachii Muscle in Time Domain Analysis
Features extraction is important for achievement in Electromyography (EMG) signals analysis. Hence, the objective of this paper is to evaluate the features extraction of EMG signals. The experimental setup for acquiring the EMG signals was based on standards that recommended by European’s surface el...
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my.utem.eprints.98932015-05-28T04:07:28Z http://eprints.utem.edu.my/id/eprint/9893/ Electromyography Signals on Biceps Brachii Muscle in Time Domain Analysis W. Daud, W. M. Bukhari T Technology (General) Features extraction is important for achievement in Electromyography (EMG) signals analysis. Hence, the objective of this paper is to evaluate the features extraction of EMG signals. The experimental setup for acquiring the EMG signals was based on standards that recommended by European’s surface electromyography for noninvasive assessment of muscle (SENIAM). The data of EMG signals were analyzed in time domain to get the features. Based on the analysis, four features have been considered based on statistical features. The average of muscle’s force condition can be estimate by correlation between sEMG voltage amplitude with linear estimation with full rectified method. These findings could be integrated to design a signal classification based on the features extraction. 2013 Article PeerReviewed application/pdf en http://eprints.utem.edu.my/id/eprint/9893/1/kertaskerjaSHPKPT.pdf W. Daud, W. M. Bukhari (2013) Electromyography Signals on Biceps Brachii Muscle in Time Domain Analysis. Prosiding Seminar Hasil Penyelidikan Sektor Pengajian Tinggi Ke-3 2013. pp. 567-578. ISSN 978-967-0334-85-1 |
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T Technology (General) W. Daud, W. M. Bukhari Electromyography Signals on Biceps Brachii Muscle in Time Domain Analysis |
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Features extraction is important for achievement in Electromyography (EMG) signals analysis. Hence, the objective of this paper is to evaluate the features extraction of EMG signals. The experimental setup for acquiring the EMG signals was based on standards that recommended by European’s surface electromyography for noninvasive assessment of muscle (SENIAM). The data of EMG signals were analyzed in time domain to get the features. Based on the analysis, four features have been considered based on statistical features. The average of muscle’s force condition can be estimate by correlation between sEMG voltage amplitude with linear estimation with full rectified method. These findings could be integrated to design a signal classification based on the features extraction. |
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Article |
author |
W. Daud, W. M. Bukhari |
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W. Daud, W. M. Bukhari |
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W. Daud, W. M. Bukhari |
title |
Electromyography Signals on Biceps Brachii Muscle in Time Domain Analysis |
title_short |
Electromyography Signals on Biceps Brachii Muscle in Time Domain Analysis |
title_full |
Electromyography Signals on Biceps Brachii Muscle in Time Domain Analysis |
title_fullStr |
Electromyography Signals on Biceps Brachii Muscle in Time Domain Analysis |
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Electromyography Signals on Biceps Brachii Muscle in Time Domain Analysis |
title_sort |
electromyography signals on biceps brachii muscle in time domain analysis |
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2013 |
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http://eprints.utem.edu.my/id/eprint/9893/1/kertaskerjaSHPKPT.pdf http://eprints.utem.edu.my/id/eprint/9893/ |
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