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EEG-based biometrics: phase-locking value from gamma band performs well across heterogeneous datasets

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dc.contributor.authorPradeep Kumar G, Utsav Dutta
dc.contributor.editorBrömme, Arslan
dc.contributor.editorDamer, Naser
dc.contributor.editorGomez-Barrero, Marta
dc.contributor.editorRaja, Kiran
dc.contributor.editorRathgeb, Christian
dc.contributor.editorSequeira Ana F.
dc.contributor.editorTodisco, Massimiliano
dc.contributor.editorUhl, Andreas
dc.date.accessioned2022-10-27T10:19:29Z
dc.date.available2022-10-27T10:19:29Z
dc.date.issued2022
dc.description.abstractThe performance of functional connectivity metrics is investigated for electroencephalogram (EEG)-based biometrics using a support vector machine classifier. Experiments are conducted on a heterogeneous EEG dataset of 184 subjects formed by pooling three distinct datasets recorded with different systems and protocols. The identification accuracy is found to be higher for higher frequency EEG bands, indicating the enhanced uniqueness of the neural signatures in beta and gamma bands. Using all the 56 EEG channels common to the three databases, the best identification accuracy of 97.4% is obtained using phase locking value-based measures extracted from the gamma frequency band. When the number of channels is reduced to 21 from 56, there is a marginal reduction of 2.4% only in the identification accuracy. Additional experiments are conducted to study the effect of the cognitive state of the subject and mismatched train/test conditions on the system performance.en
dc.identifier.doi10.1109/BIOSIG55365.2022.9897042
dc.identifier.isbn978-3-88579-723-4
dc.identifier.pissn1617-5492
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/39702
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofBIOSIG 2022
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-329
dc.subjectbiometrics
dc.subjectEEG
dc.subjectfunctional connectivity
dc.subjectphase locking value
dc.subjectsupport vector machine
dc.titleEEG-based biometrics: phase-locking value from gamma band performs well across heterogeneous datasetsen
dc.typeText/Conference Paper
gi.citation.endPage252
gi.citation.publisherPlaceBonn
gi.citation.startPage245
gi.conference.date14.-16. September 2022
gi.conference.locationDarmstadt
gi.conference.sessiontitleFurther Conference Contributions

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P329 - BIOSIG 2022 - Proceedings of the 21st International Conference of the Biometrics Special Interest Group