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EEG based user recognition using BUMP modelling

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dc.contributor Universitat de Vic. Escola Politècnica Superior
dc.contributor Universitat de Vic. Grup de Recerca en Tecnologies Digitals
dc.contributor International Conference of the Biometrics Special Interest Group, BIOSIG 2013 (12 : 2013 : Alemanya)
dc.contributor.author La Rocca, D.
dc.contributor.author Campisi, P.
dc.contributor.author Solé-Casals, Jordi
dc.date.accessioned 2014-02-14T08:48:44Z
dc.date.available 2014-02-14T08:48:44Z
dc.date.created 2013
dc.date.issued 2013
dc.identifier.citation Rocca, D. L., Campisi, P., & Sole-Casals, J. (2013). EEG based user recognition using BUMP modelling. Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft Fur Informatik (GI), Germany. , P-212; Darmstadt ca_ES
dc.identifier.isbn 978-388579606-0
dc.identifier.issn 16175468
dc.identifier.uri http://hdl.handle.net/10854/2715
dc.description.abstract In this paper the use of electroencephalogram (EEG) as biometric identifier is investigated. The use of EEG within the biometric framework has already been introduced in the recent past although it has not been extensively analyzed. In this contribution we apply the 'bump' modelling analysis for the feature extraction stage within an identification framework, in order to reduce the huge amount of data recorded through EEG. For the purpose of this study we rely on the 'resting state with eyes closed' protocol. The employed database is composed of 36 healthy subjects whose EEG signals have been acquired in an ad hoc laboratory. Different electrodes configurations pertinent with the employed protocol have been considered. A classifier based on Mahalanobis distance have been tested for the enrollment of the subjects and their identification. An information fusion performed at the score level has shown to improve correct classification performance. The obtained results show that an identification accuracy of 99.69% can be achieved. It represents an high degree of accuracy, given the current state of research on EEG biometrics. © 2013 Gesellschaft für Informatik e.V. (GI). ca_ES
dc.format application/pdf
dc.format.extent 12 p. ca_ES
dc.language.iso eng ca_ES
dc.publisher IEEE ca_ES
dc.rights Tots els drets reservats ca_ES
dc.rights c) IEEE, 2013 Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.subject.other Electroencefalografia ca_ES
dc.subject.other Tractament del senyal ca_ES
dc.title EEG based user recognition using BUMP modelling ca_ES
dc.type info:eu-repo/semantics/conferenceObject ca_ES
dc.relation.publisherversion http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6617154&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D6617154
dc.rights.accesRights info:eu-repo/semantics/closedAccess ca_ES
dc.indexacio Indexat a SCOPUS

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