SEMG signal processing and analysis using wavelet transform and higher order statistics to characterize muscle force

An algorithm is proposed for processing and analyzing surface electromyography (SEMG) signals using wavelet transform and Higher Order Statistics (HOS). EMG signal acquires noise while travelling though different media. Wavelet denoising is performed in this research for initial EMG signal proces...

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Bibliographic Details
Main Authors:	Hussain, M. S., Reaz, Mamun Ibn, Ibrahimy, Muhammad Ibn
Format:	Conference or Workshop Item
Language:	English
Published:	2008
Subjects:	T Technology (General)
Online Access:	http://irep.iium.edu.my/36225/ http://irep.iium.edu.my/36225/ http://irep.iium.edu.my/36225/1/WSEAS_Sys1-59.pdf

id	iium-36225
recordtype	eprints
spelling	iium-362252014-04-16T01:58:57Z http://irep.iium.edu.my/36225/ SEMG signal processing and analysis using wavelet transform and higher order statistics to characterize muscle force Hussain, M. S. Reaz, Mamun Ibn Ibrahimy, Muhammad Ibn T Technology (General) An algorithm is proposed for processing and analyzing surface electromyography (SEMG) signals using wavelet transform and Higher Order Statistics (HOS). EMG signal acquires noise while travelling though different media. Wavelet denoising is performed in this research for initial EMG signal processing. With the appropriate choice of the Wavelet Function (WF), it is possible to remove interference noise effectively. Root Mean Square (RMS) difference and Signal to Noise Ratio (SNR) values are calculated to determine the most suitable WF. Results show that WF db2 performs denoising best among the other wavelets. Power spectrum analysis is performed to the denoised SEMG to indicate changes in muscle contraction. Furthermore, HOS method is applied for further efficient processing due to the unique properties of HOS applied to random time series. Gaussianity and linearity tests are conducted as part of HOS which shows that SEMG signal becomes less gaussian and more linear with increased force. 2008 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/36225/1/WSEAS_Sys1-59.pdf Hussain, M. S. and Reaz, Mamun Ibn and Ibrahimy, Muhammad Ibn (2008) SEMG signal processing and analysis using wavelet transform and higher order statistics to characterize muscle force. In: 12th WSEAS International Conference on SYSTEMS, 22-24 July 2008, Heraklion, Greece. http://www.wseas.us/e-library/conferences/2008/crete/Systems/sys1-59.pdf
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	T Technology (General)
spellingShingle	T Technology (General) Hussain, M. S. Reaz, Mamun Ibn Ibrahimy, Muhammad Ibn SEMG signal processing and analysis using wavelet transform and higher order statistics to characterize muscle force
description	An algorithm is proposed for processing and analyzing surface electromyography (SEMG) signals using wavelet transform and Higher Order Statistics (HOS). EMG signal acquires noise while travelling though different media. Wavelet denoising is performed in this research for initial EMG signal processing. With the appropriate choice of the Wavelet Function (WF), it is possible to remove interference noise effectively. Root Mean Square (RMS) difference and Signal to Noise Ratio (SNR) values are calculated to determine the most suitable WF. Results show that WF db2 performs denoising best among the other wavelets. Power spectrum analysis is performed to the denoised SEMG to indicate changes in muscle contraction. Furthermore, HOS method is applied for further efficient processing due to the unique properties of HOS applied to random time series. Gaussianity and linearity tests are conducted as part of HOS which shows that SEMG signal becomes less gaussian and more linear with increased force.
format	Conference or Workshop Item
author	Hussain, M. S. Reaz, Mamun Ibn Ibrahimy, Muhammad Ibn
author_facet	Hussain, M. S. Reaz, Mamun Ibn Ibrahimy, Muhammad Ibn
author_sort	Hussain, M. S.
title	SEMG signal processing and analysis using wavelet transform and higher order statistics to characterize muscle force
title_short	SEMG signal processing and analysis using wavelet transform and higher order statistics to characterize muscle force
title_full	SEMG signal processing and analysis using wavelet transform and higher order statistics to characterize muscle force
title_fullStr	SEMG signal processing and analysis using wavelet transform and higher order statistics to characterize muscle force
title_full_unstemmed	SEMG signal processing and analysis using wavelet transform and higher order statistics to characterize muscle force
title_sort	semg signal processing and analysis using wavelet transform and higher order statistics to characterize muscle force
publishDate	2008
url	http://irep.iium.edu.my/36225/ http://irep.iium.edu.my/36225/ http://irep.iium.edu.my/36225/1/WSEAS_Sys1-59.pdf
first_indexed	2023-09-18T20:51:50Z
last_indexed	2023-09-18T20:51:50Z
_version_	1777410046356881408

SEMG signal processing and analysis using wavelet transform and higher order statistics to characterize muscle force

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