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Exploring The Relation Between EMG Pattern Recognition And Sampling Rate Using Spectrogram

The application of electromyography (EMG) has shown great success in rehabilitation engineering. With the existing multiple-channel EMG recording system, the detection and classification of EMG pattern have become viable. The purpose of this study is to investigate the relation between sampling rate...

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Main Authors: Abdullah, Abdul Rahim, Too, Jing Wei, Mohd Ali, Nursabillilah, Tengku Zawawi, Tengku Nor Shuhada, Mohd Saad, Norhashimah
Format: Article
Language:English
Published: Korean Institute of Electrical Engineers 2019
Online Access:http://eprints.utem.edu.my/id/eprint/24621/2/2019%20EXPLORING%20THE%20RELATION%20BETWEEN%20EMG%20PATTERN%20RECOGNITION%20AND%20SAMPLING%20RATE%20USING%20SPECTROGRAM.PDF
http://eprints.utem.edu.my/id/eprint/24621/
https://link.springer.com/article/10.1007/s42835-019-00083-3
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spelling my.utem.eprints.246212020-12-08T13:07:26Z http://eprints.utem.edu.my/id/eprint/24621/ Exploring The Relation Between EMG Pattern Recognition And Sampling Rate Using Spectrogram Abdullah, Abdul Rahim Too, Jing Wei Mohd Ali, Nursabillilah Tengku Zawawi, Tengku Nor Shuhada Mohd Saad, Norhashimah The application of electromyography (EMG) has shown great success in rehabilitation engineering. With the existing multiple-channel EMG recording system, the detection and classification of EMG pattern have become viable. The purpose of this study is to investigate the relation between sampling rate and EMG pattern recognition by using spectrogram. The features are extracted from spectrogram coefficients and the principal component analysis is applied for dimensionality reduction. In addition, the optimal Hanning window size is identified and selected before performance evaluation. For noise evaluation, the additive white Gaussian noise (AGWN) is added to the EMG signal at 30, 25, 20 dB SNR. The results illustrated that the 512 Hz sampling rate can maintain a small decrement of 0.76% accuracy compared to 1024 Hz. However, when the AGWN is added, the 256 and 512 Hz sampling rates showed a greater reduction in overall classification performance. For a lower SNR, the gaps in classification accuracy between 1024 Hz, 512 Hz and 256 Hz sampling rates are obviously presented. It signifies that reducing the sampling rate lower than 1024 Hz might not be a good choice since the noise and artifact have to be taken into consideration in a real system. Korean Institute of Electrical Engineers 2019-03 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/24621/2/2019%20EXPLORING%20THE%20RELATION%20BETWEEN%20EMG%20PATTERN%20RECOGNITION%20AND%20SAMPLING%20RATE%20USING%20SPECTROGRAM.PDF Abdullah, Abdul Rahim and Too, Jing Wei and Mohd Ali, Nursabillilah and Tengku Zawawi, Tengku Nor Shuhada and Mohd Saad, Norhashimah (2019) Exploring The Relation Between EMG Pattern Recognition And Sampling Rate Using Spectrogram. Journal of Electrical Engineering and Technology, 14 (2). pp. 947-953. ISSN 1975-0102 https://link.springer.com/article/10.1007/s42835-019-00083-3 10.1007/s42835-019-00083-3
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
description The application of electromyography (EMG) has shown great success in rehabilitation engineering. With the existing multiple-channel EMG recording system, the detection and classification of EMG pattern have become viable. The purpose of this study is to investigate the relation between sampling rate and EMG pattern recognition by using spectrogram. The features are extracted from spectrogram coefficients and the principal component analysis is applied for dimensionality reduction. In addition, the optimal Hanning window size is identified and selected before performance evaluation. For noise evaluation, the additive white Gaussian noise (AGWN) is added to the EMG signal at 30, 25, 20 dB SNR. The results illustrated that the 512 Hz sampling rate can maintain a small decrement of 0.76% accuracy compared to 1024 Hz. However, when the AGWN is added, the 256 and 512 Hz sampling rates showed a greater reduction in overall classification performance. For a lower SNR, the gaps in classification accuracy between 1024 Hz, 512 Hz and 256 Hz sampling rates are obviously presented. It signifies that reducing the sampling rate lower than 1024 Hz might not be a good choice since the noise and artifact have to be taken into consideration in a real system.
format Article
author Abdullah, Abdul Rahim
Too, Jing Wei
Mohd Ali, Nursabillilah
Tengku Zawawi, Tengku Nor Shuhada
Mohd Saad, Norhashimah
spellingShingle Abdullah, Abdul Rahim
Too, Jing Wei
Mohd Ali, Nursabillilah
Tengku Zawawi, Tengku Nor Shuhada
Mohd Saad, Norhashimah
Exploring The Relation Between EMG Pattern Recognition And Sampling Rate Using Spectrogram
author_facet Abdullah, Abdul Rahim
Too, Jing Wei
Mohd Ali, Nursabillilah
Tengku Zawawi, Tengku Nor Shuhada
Mohd Saad, Norhashimah
author_sort Abdullah, Abdul Rahim
title Exploring The Relation Between EMG Pattern Recognition And Sampling Rate Using Spectrogram
title_short Exploring The Relation Between EMG Pattern Recognition And Sampling Rate Using Spectrogram
title_full Exploring The Relation Between EMG Pattern Recognition And Sampling Rate Using Spectrogram
title_fullStr Exploring The Relation Between EMG Pattern Recognition And Sampling Rate Using Spectrogram
title_full_unstemmed Exploring The Relation Between EMG Pattern Recognition And Sampling Rate Using Spectrogram
title_sort exploring the relation between emg pattern recognition and sampling rate using spectrogram
publisher Korean Institute of Electrical Engineers
publishDate 2019
url http://eprints.utem.edu.my/id/eprint/24621/2/2019%20EXPLORING%20THE%20RELATION%20BETWEEN%20EMG%20PATTERN%20RECOGNITION%20AND%20SAMPLING%20RATE%20USING%20SPECTROGRAM.PDF
http://eprints.utem.edu.my/id/eprint/24621/
https://link.springer.com/article/10.1007/s42835-019-00083-3
_version_ 1687397252477222912
score 13.211869

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