Source identification and separation using sub-band ICA of sEMG

Ganesh R. Naik, Dinesh K. Kumar, Marimuthu Palaniswami

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

Source identification and separation of number of active muscles during a complex action is useful information to identify the action, and to determine pathologies. Biosignals such as surface electromyogram are a result of the summation of electrical activity of a number of sources. The complexity of the anatomy and actions results difficulty in identifying the number of active sources from the multiple channel recordings. ICA has been applied to sEMG to separate the signals originating from different sources. But it is often difficult to determine the number of active sources that may vary between different actions and gestures. This paper reports research conducted to evaluate the use of sub-band ICA for the separation of bioelectric signals when the number of active sources may not be known. The paper proposes the use of value of the determinant of the global matrix generated using sub-band ICA for identifying the number of active sources. The results indicate that the technique is successful in identifying the number of active muscles for complex hand gestures.

Original languageEnglish
Title of host publicationTENCON 2008 - 2008 IEEE Region 10 Conference
Place of PublicationHyderabad
PublisherIEEE
Pages1-6
Number of pages6
ISBN (Print)1424424089, 9781424424085
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event2008 IEEE Region 10 Conference, TENCON 2008 - Hyderabad, India
Duration: 19 Nov 200821 Nov 2008

Publication series

NameIEEE Region 10 Annual International Conference, Proceedings/TENCON

Conference

Conference2008 IEEE Region 10 Conference, TENCON 2008
CountryIndia
CityHyderabad
Period19/11/0821/11/08

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