A comparison of ICA algorithms in surface EMG signal processing

Naik, GR

A comparison of ICA algorithms in surface EMG signal processing

Naik, GR

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Publication Type:: Journal Article
Citation:: International Journal of Biomedical Engineering and Technology, 2011, 6 (4), pp. 363 - 374
Issue Date:: 2011-08-01

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Field	Value	Language
dc.contributor.author	Naik, GR https://orcid.org/0000-0003-1790-9838	en_US
dc.date.issued	2011-08-01	en_US
dc.identifier.citation	International Journal of Biomedical Engineering and Technology, 2011, 6 (4), pp. 363 - 374	en_US
dc.identifier.issn	1752-6418	en_US
dc.identifier.uri	http://hdl.handle.net/10453/27574
dc.description.abstract	Recent research has resulted in development of number of different Independent Component Analysis (ICA) technique. While there are some researchers who have compared their techniques with the existing methods for audio examples, there is no comparison of performance between ICA algorithms for biosignal applications. With ICA being the feasible method for source separation and decomposition of biosignals, it is important to compare the different techniques and determine the most suitable method for the applications. This paper presents the performance of five ICA algorithms (SOBI, TDSEP, FastICA, JADE and Infomax) for decomposition of surface electromyogram (sEMG) to identify subtle wrist actions. Copyright © 2011 Inderscience Enterprises Ltd.	en_US
dc.relation.ispartof	International Journal of Biomedical Engineering and Technology	en_US
dc.relation.isbasedon	10.1504/IJBET.2011.041774	en_US
dc.title	A comparison of ICA algorithms in surface EMG signal processing	en_US
dc.type	Journal Article
utslib.citation.volume	4	en_US
utslib.citation.volume	6	en_US
utslib.for	0903 Biomedical Engineering	en_US
utslib.for	0802 Computation Theory and Mathematics	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access
pubs.issue	4	en_US
pubs.publication-status	Published	en_US
pubs.volume	6	en_US

Abstract:

Recent research has resulted in development of number of different Independent Component Analysis (ICA) technique. While there are some researchers who have compared their techniques with the existing methods for audio examples, there is no comparison of performance between ICA algorithms for biosignal applications. With ICA being the feasible method for source separation and decomposition of biosignals, it is important to compare the different techniques and determine the most suitable method for the applications. This paper presents the performance of five ICA algorithms (SOBI, TDSEP, FastICA, JADE and Infomax) for decomposition of surface electromyogram (sEMG) to identify subtle wrist actions. Copyright © 2011 Inderscience Enterprises Ltd.

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http://hdl.handle.net/10453/27574