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dc.contributor.authorS. Daochaien_US
dc.contributor.authorD. Sueaseenaken_US
dc.contributor.authorT. Chanwimalueangen_US
dc.contributor.authorN. Laoopugsinen_US
dc.contributor.authorC. Pintaviroojen_US
dc.contributor.otherMahidol Universityen_US
dc.contributor.otherSrinakharinwirot Universityen_US
dc.contributor.otherKing Mongkut's Institute of Technology Ladkrabangen_US
dc.date.accessioned2018-08-24T01:48:03Z-
dc.date.available2018-08-24T01:48:03Z-
dc.date.issued2007-12-01en_US
dc.identifier.citation2007 6th International Conference on Information, Communications and Signal Processing, ICICS. (2007)en_US
dc.identifier.other2-s2.0-50449111058en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=50449111058&origin=inwarden_US
dc.identifier.urihttp://repository.li.mahidol.ac.th/dspace/handle/123456789/24389-
dc.description.abstractWe develop a multi-channel electromyogram acquisition system using PSOC microcontroller to aquire multichannel EMG signals. An array of 4 x 4 surface electrodes is used to record the EMG signal. B-spline interpolation technique has been utilized to map the EMG signal on the muscle surface. The topological mapping of the EMG is then analyzed to classify the pattern of muscle contraction. The proposed system was successfully demonstrated to record EMG data and its surface mapping. The muscular contraction classification of mapping using independent component analysis demonstrates promising results. ©2007 IEEE.en_US
dc.rightsMahidol Universityen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=50449111058&origin=inwarden_US
dc.subjectComputer Scienceen_US
dc.titleIndependent component analysis: An application for muscular contraction classificationen_US
dc.typeConference Paperen_US
dc.rights.holderSCOPUSen_US
dc.identifier.doi10.1109/ICICS.2007.4449674en_US
Appears in Collections:Scopus 2006-2010

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