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Electrocorticogram as the Basis for a Direct Brain Interface: Opportunities for Improved Detection Accuracy

dc.contributor.authorHuggins, J. E.en_US
dc.contributor.authorLevine, S. P.en_US
dc.contributor.authorFessler, Jeffrey A.en_US
dc.contributor.authorSowers, W. M.en_US
dc.contributor.authorPfurtscheller, G.en_US
dc.contributor.authorGraimann, B.en_US
dc.contributor.authorSchloegl, A.en_US
dc.contributor.authorMinecan, Danielaen_US
dc.contributor.authorKushwaha, R. K.en_US
dc.contributor.authorBeMent, S. L.en_US
dc.contributor.authorSagher, O.en_US
dc.contributor.authorSchuh, L. A.en_US
dc.date.accessioned2011-08-18T18:21:19Z
dc.date.available2011-08-18T18:21:19Z
dc.date.issued2003-03-20en_US
dc.identifier.citationHuggins, J.E. ; Levine, S.P. ; Fessler, J.A. ; Sowers, W.M. ; Pfurtscheller, G. ; Graimann, B. ; Schloegl, A. ; Minecan, D.N. ; Kushwaha, R.K. ; BeMent, S.L. ; Sagher, O. ; Schuh, L.A. (2003). "Electrocorticogram as the Basis for a Direct Brain Interface: Opportunities for Improved Detection Accuracy." International IEEE EMBS Conference on Neural Engineering: 587-590. <http://hdl.handle.net/2027.42/85993>en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/85993
dc.description.abstractA direct brain interface (DBI) based on the detection of event-related potentials (ERPs) in human electrocorticogram (ECoG) is under development. Accurate detection has been demonstrated with this approach (near 100% on a few channels) using a single-channel cross-correlation template matching (CCTM) method. Several opportunities for improved detection accuracy have been identified. Detection using a multiple-channel CCTM method and a variety of detection methods that take advantage of the simultaneous occurrence of ERPs and event-related desynchronization/synchronization (ERD/ERS) have been demonstrated to offer potential for improved detection accuracy.en_US
dc.publisherIEEEen_US
dc.titleElectrocorticogram as the Basis for a Direct Brain Interface: Opportunities for Improved Detection Accuracyen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelBiomedical Engineeringen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationotherDepartment of Medical Informatics, Institute for Biomedical Engineering, University of Technology, Graz, Austria. Ludwig Boltzmann Institute of Medical Informatics and Neuroinformatics, Graz, Austria. Henry Ford Hospital, Detroit, Michigan, USA.en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/85993/1/Fessler183.pdf
dc.identifier.doi10.1109/CNE.2003.1196896en_US
dc.identifier.sourceInternational IEEE EMBS Conference on Neural Engineeringen_US
dc.owningcollnameElectrical Engineering and Computer Science, Department of (EECS)


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