Source separation techniques for optimal electrode configurations: A study on electromyography

Naik, GR; Kumar, DK; Weghorn, H; Arjunan, SP

Source separation techniques for optimal electrode configurations: A study on electromyography

Naik, GR

Kumar, DK Weghorn, H Arjunan, SP

Permalink

Publication Type:: Journal Article
Citation:: Journal of Medical and Biological Engineering, 2010, 30 (6), pp. 367 - 372
Issue Date:: 2010-12-01

Closed Access

	Filename	Description	Size
	2012007344OK.pdf		1.23 MB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Naik, GR https://orcid.org/0000-0003-1790-9838	en_US
dc.contributor.author	Kumar, DK	en_US
dc.contributor.author	Weghorn, H	en_US
dc.contributor.author	Arjunan, SP	en_US
dc.date.issued	2010-12-01	en_US
dc.identifier.citation	Journal of Medical and Biological Engineering, 2010, 30 (6), pp. 367 - 372	en_US
dc.identifier.issn	1609-0985	en_US
dc.identifier.uri	http://hdl.handle.net/10453/26654
dc.description.abstract	Surface electromyography (sEMG) is used to study underlying muscle activity. However, due to anatomical complexity, there is cross-talk, and the recorded sEMG corresponds to the mix of activities of different muscles. To overcome this, studies have attempted the use of blind source separation (BSS) and also the use of arrays of electrodes to identify activity of individual muscles. However, it is difficult to determine the most appropriate set of electrodes due to the dependency between the various channels. This paper describes a method by which it is possible to identify the dependency between the various channels, and thus the most appropriate set of channels can be identified. This study has investigated different configurations of electrodes for accurate identification of different hand gestures required for human-computer interface application.	en_US
dc.relation.ispartof	Journal of Medical and Biological Engineering	en_US
dc.relation.isbasedon	10.5405/jmbe.780	en_US
dc.subject.classification	Biomedical Engineering	en_US
dc.title	Source separation techniques for optimal electrode configurations: A study on electromyography	en_US
dc.type	Journal Article
utslib.citation.volume	6	en_US
utslib.citation.volume	30	en_US
utslib.for	090609 Signal Processing	en_US
utslib.for	090302 Biomechanical Engineering	en_US
utslib.for	090399 Biomedical Engineering not elsewhere classified	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	0903 Biomedical Engineering	en_US
utslib.for	0906 Electrical and Electronic Engineering	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	6	en_US
pubs.publication-status	Published	en_US
pubs.volume	30	en_US

Abstract:

Surface electromyography (sEMG) is used to study underlying muscle activity. However, due to anatomical complexity, there is cross-talk, and the recorded sEMG corresponds to the mix of activities of different muscles. To overcome this, studies have attempted the use of blind source separation (BSS) and also the use of arrays of electrodes to identify activity of individual muscles. However, it is difficult to determine the most appropriate set of electrodes due to the dependency between the various channels. This paper describes a method by which it is possible to identify the dependency between the various channels, and thus the most appropriate set of channels can be identified. This study has investigated different configurations of electrodes for accurate identification of different hand gestures required for human-computer interface application.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/26654