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Resting-state EEG: A Study on its non-Stationarity for Biometric Applicaions

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dc.contributor.authorHine, Gabriel Emile
dc.contributor.authorMaiorana, Emanuele
dc.contributor.authorCampisi,Patrizio
dc.contributor.editorBrömme,Arslan
dc.contributor.editorBusch,Christoph
dc.contributor.editorDantcheva,Antitza
dc.contributor.editorRathgeb,Christian
dc.contributor.editorUhl,Andreas
dc.date.accessioned2017-09-26T09:20:58Z
dc.date.available2017-09-26T09:20:58Z
dc.date.issued2017
dc.description.abstractIn the last years, several papers on EEG-based biometric recognition systems have been published. Specifically, most of the proposed contributions focus on brain signals recorded in resting state conditions, with either closed or open eyes. A common assumption is that the acquired signals are quasi-stationarity. In this paper, we investigate such property in terms of discriminative capability, and we analyze whether or not it holds throughout the entire duration of data collected over long periods. An extensive set of experimental tests, conducted over a database comprising signals collected from 50 subjects in three distinct acquisition sessions, shows that the most distinctive information of the brain signals is temporally located at the beginning of each recording.en
dc.identifier.isbn978-3-88579-664-0
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/4639
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofBIOSIG 2017
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-70
dc.subjectEEG
dc.subjectBiometrics
dc.subjectnon-Stationarity
dc.titleResting-state EEG: A Study on its non-Stationarity for Biometric Applicaionsen
gi.citation.endPage23
gi.citation.startPage15
gi.conference.date20.-22. September 2017
gi.conference.locationDarmstadt, Germany
gi.conference.sessiontitleRegular Research Papers

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P270 - BIOSIG 2017 - Proceedings of the 16th International Conference of the Biometrics Special Interest Group