Classification of multichannel ECoG related to individual finger movements with redundant spatial projections

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buir.contributor.authorÇetin, A. Enis
buir.contributor.orcidÇetin, A. Enis|0000-0002-3449-1958
dc.citation.epage5427en_US
dc.citation.spage5424en_US
dc.contributor.authorOnaran, ibrahimen_US
dc.contributor.authorİnce, N. Fıraten_US
dc.contributor.authorÇetin, A. Enisen_US
dc.coverage.spatialBoston, MA, USAen_US
dc.date.accessioned2016-02-08T12:15:19Z
dc.date.available2016-02-08T12:15:19Z
dc.date.issued2011en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.departmentDepartment of Computer Engineeringen_US
dc.descriptionDate of Conference: 30 Aug.-3 Sept. 2011en_US
dc.description.abstractWe tackle the problem of classifying multichannel electrocorticogram (ECoG) related to individual finger movements for a brain machine interface (BMI). For this particular aim we applied a recently developed hierarchical spatial projection framework of neural activity for feature extraction from ECoG. The algorithm extends the binary common spatial patterns algorithm to multiclass problem by constructing a redundant set of spatial projections that are tuned for paired and group-wise discrimination of finger movements. The groupings were constructed by merging the data of adjacent fingers and contrasting them to the rest, such as the first two fingers (thumb and index) vs. the others (middle, ring and little). We applied this framework to the BCI competition IV ECoG data recorded from three subjects. We observed that the maximum classification accuracy was obtained from the gamma frequency band (65200Hz). For this particular frequency range the average classification accuracy over three subjects was 86.3%. These results indicate that the redundant spatial projection framework can be used successfully in decoding finger movements from ECoG for BMI. © 2011 IEEE.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T12:15:19Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2011en
dc.identifier.doi10.1109/IEMBS.2011.6091341en_US
dc.identifier.urihttp://hdl.handle.net/11693/28248
dc.language.isoEnglishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/IEMBS.2011.6091341en_US
dc.source.title2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Societyen_US
dc.subjectBrain machine interfaceen_US
dc.subjectClassification accuracyen_US
dc.subjectCommon spatial patternsen_US
dc.subjectElectrocorticogramen_US
dc.subjectFinger movementsen_US
dc.subjectFrequency rangesen_US
dc.subjectMulti-channelen_US
dc.subjectMulti-class problemsen_US
dc.subjectNeural activityen_US
dc.subjectAlgorithmsen_US
dc.subjectFeature extractionen_US
dc.subjectFrequency bandsen_US
dc.subjectElectrophysiologyen_US
dc.titleClassification of multichannel ECoG related to individual finger movements with redundant spatial projectionsen_US
dc.typeConference Paperen_US

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