Efficient and Accurate Neural Fingerprints Obtained via Mean Curve Length of High Dimensional Model Representation of EEG Signals

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dc.contributor.authorOzay E.K.
dc.contributor.authorOzkurt T.E.
dc.date.accessioned2024-03-13T10:00:55Z
dc.date.available2024-03-13T10:00:55Z
dc.date.issued2023
dc.departmentİstanbul Beykent Üniversitesien_US
dc.description31st European Signal Processing Conference, EUSIPCO 2023 -- 4 September 2023 through 8 September 2023 -- -- 194070en_US
dc.description.abstractIn this study, we propose and evaluate a feature extraction methodology for the purpose of EEG-based person recognition. To this end, the mean curve length (MCL) was employed subsequent to the representation of EEG signals in an orthogonal geometry through High Dimensional Model Representation (HDMR). To analyze the effectiveness of the methodology, we executed it on a standard publicly available EEG dataset containing 109 subjects and acquired from 64 channels for eyes-open (EO) and eyes-closed (EC) resting-state conditions. The proposed feature was evaluated by comparing it to MCL, beta, and gamma band activities. According to the performance results, applying MCL to the output of the HDMR instead of raw data provides superior performances for identification and authentication. The attained results promise a novel simple, fast, and accurate biometric recognition scheme, named HDMRMCL. © 2023 European Signal Processing Conference, EUSIPCO. All rights reserved.en_US
dc.identifier.doi10.23919/EUSIPCO58844.2023.10290000
dc.identifier.endpage1179en_US
dc.identifier.isbn9789464593600
dc.identifier.issn2219-5491
dc.identifier.scopus2-s2.0-85178357767
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage1175en_US
dc.identifier.urihttps://doi.org/10.23919/EUSIPCO58844.2023.10290000
dc.identifier.urihttps://hdl.handle.net/20.500.12662/2867
dc.indekslendigikaynakScopus
dc.language.isoenen_US
dc.publisherEuropean Signal Processing Conference, EUSIPCOen_US
dc.relation.ispartofEuropean Signal Processing Conferenceen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectauthenticationen_US
dc.subjectbiometricsen_US
dc.subjectEEGen_US
dc.subjectHDMRen_US
dc.subjectidentificationen_US
dc.subjectmean curve lengthen_US
dc.subjectresting-stateen_US
dc.titleEfficient and Accurate Neural Fingerprints Obtained via Mean Curve Length of High Dimensional Model Representation of EEG Signalsen_US
dc.typeConference Objecten_US

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