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Conference Paper: Second order statistics based blind source separation for artifact correction of short ERP epochs

TitleSecond order statistics based blind source separation for artifact correction of short ERP epochs
Authors
Ting, KHChang, CLeung, AWSChan, CCHFung, PCWChan, FHY
KeywordsEEG
EM
Artifact Correction
Blind Source Separation
Second Order Statistics
Issue Date2003
PublisherIEEE.
Citation
IEEE - E M B S Asian-Pacific Conference on Biomedical Engineering, Kyoto-Osaka-Nara, JAPAN, 20-22 October 2003, p. 186-187 How to Cite?
DOI: http://dx.doi.org/10.1109/APBME.2003.1302646
AbstractERP is commonly obtained by averaging over segmented EEC epochs. In case artifacts are present in the raw EEC measurement, pre-processing is required to prevent the averaged ERP waveform being interfered by artifacts. The simplest pre-processing approach is by rejecting trials in which presence of artifact is detected. Alternatively artifact correction instead of rejection can be performed by blind source separation, so that waste of ERP trials is avoided. In this paper, we propose a second order statistics based blind source separation approach to ERP artifact correction. Comparing with blind separation using independent component analysis, second order statistics based method does not rely on higher order statistics or signal entropy, and therefore leads to more robust separation even if only short epochs are available.
Persistent Identifierhttp://hdl.handle.net/10722/46506

 

DC FieldValueLanguage
dc.contributor.authorTing, KHen_HK
dc.contributor.authorChang, Cen_HK
dc.contributor.authorLeung, AWSen_HK
dc.contributor.authorChan, CCHen_HK
dc.contributor.authorFung, PCWen_HK
dc.contributor.authorChan, FHYen_HK
dc.date.accessioned2007-10-30T06:51:30Z-
dc.date.available2007-10-30T06:51:30Z-
dc.date.issued2003en_HK
dc.identifier.citationIEEE - E M B S Asian-Pacific Conference on Biomedical Engineering, Kyoto-Osaka-Nara, JAPAN, 20-22 October 2003, p. 186-187en_HK
dc.identifier.urihttp://hdl.handle.net/10722/46506-
dc.description.abstractERP is commonly obtained by averaging over segmented EEC epochs. In case artifacts are present in the raw EEC measurement, pre-processing is required to prevent the averaged ERP waveform being interfered by artifacts. The simplest pre-processing approach is by rejecting trials in which presence of artifact is detected. Alternatively artifact correction instead of rejection can be performed by blind source separation, so that waste of ERP trials is avoided. In this paper, we propose a second order statistics based blind source separation approach to ERP artifact correction. Comparing with blind separation using independent component analysis, second order statistics based method does not rely on higher order statistics or signal entropy, and therefore leads to more robust separation even if only short epochs are available.en_HK
dc.format.extent161746 bytes-
dc.format.extent4066 bytes-
dc.format.extent13817 bytes-
dc.format.extent3485 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.format.mimetypetext/plain-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.rights©2003 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.subjectEEGen_HK
dc.subjectEMen_HK
dc.subjectArtifact Correctionen_HK
dc.subjectBlind Source Separationen_HK
dc.subjectSecond Order Statisticsen_HK
dc.titleSecond order statistics based blind source separation for artifact correction of short ERP epochsen_HK
dc.typeConference_Paperen_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/APBME.2003.1302646en_HK
dc.identifier.scopuseid_2-s2.0-56649088632-
dc.identifier.hkuros95132-

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