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A novel human identification system based on electrocardiogram features

dc.contributor.authorGürkan, Hakanen_US
dc.contributor.authorGüz, Ümiten_US
dc.contributor.authorYarman, Bekir Sıddık Binboğaen_US
dc.date.accessioned2015-07-14T23:46:48Z
dc.date.available2015-07-14T23:46:48Z
dc.date.issued2013
dc.identifier.citationGürkan, H., Güz, Ü., & Yarman, B. S. B. (2013). A novel human identification system based on electrocardiogram features. Paper presented at the International Symposium on Signals, Circuits and Systems ISSCS2013, 1-4. doi:10.1109/ISSCS.2013.6651266en_US
dc.identifier.isbn9781467361415
dc.identifier.isbn9781479931934
dc.identifier.isbn9781467361439
dc.identifier.urihttps://hdl.handle.net/11729/599
dc.identifier.urihttp://dx.doi.org/10.1109/ISSCS.2013.6651266
dc.descriptionThe work is supported by The Scientific Research Fund of ISIK University (Project Number: 10A301)en_US
dc.description.abstractIn this work, we present a novel biometric authentication approach based on combination of AC/DCT features, MFCC features, and QRS beat information of the ECG signals. The proposed approach is tested on a subset of 30 subjects selected from the PTB database. This subset consists of 13 healthy and 17 non-healthy subjects who have two ECG records. The proposed biometric authentication approach achieves average frame recognition rate of %97.31 on the selected subset. Our experimental results imply that the frame recognition rate of the proposed authentication approach is better than that of ACDCT and MFCC based biometric authentication systems, individually.en_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.relation.isversionof10.1109/ISSCS.2013.6651266
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectECGen_US
dc.subjectHuman identificationen_US
dc.subjectFeature extractionen_US
dc.subjectAuthenticationen_US
dc.subjectBand-pass filtersen_US
dc.subjectDatabasesen_US
dc.subjectDiscrete cosine transformsen_US
dc.subjectElectrocardiographyen_US
dc.subjectMel frequency cepstral coefficienten_US
dc.subjectAC-DCT feature extractionen_US
dc.subjectACDCT based biometric authentication systemen_US
dc.subjectECG signalen_US
dc.subjectMFCC based biometric authentication systemen_US
dc.subjectMFCC feature extractionen_US
dc.subjectPTB databaseen_US
dc.subjectQRS beat informationen_US
dc.subjectAverage frame recognition rateen_US
dc.subjectBiometric authentication approachen_US
dc.subjectElectrocardiogram feature extractionen_US
dc.subjectHuman identification systemen_US
dc.subjectBioelectric potentialsen_US
dc.subjectCryptographic protocolsen_US
dc.subjectMedical signal detectionen_US
dc.subjectMedical signal processingen_US
dc.titleA novel human identification system based on electrocardiogram featuresen_US
dc.typeconferenceObjecten_US
dc.description.versionPublisher's Versionen_US
dc.relation.journalInternational Symposium on Signals, Circuits and Systems ISSCS2013en_US
dc.contributor.departmentIşık Üniversitesi, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.contributor.departmentIşık University, Faculty of Engineering, Department of Electrical-Electronics Engineeringen_US
dc.contributor.authorID0000-0002-7008-4778
dc.contributor.authorID0000-0002-4597-0954
dc.identifier.startpage1
dc.identifier.endpage4
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.contributor.institutionauthorGürkan, Hakanen_US
dc.contributor.institutionauthorGüz, Ümiten_US
dc.relation.indexWOSen_US
dc.relation.indexScopusen_US
dc.relation.indexConference Proceedings Citation Index – Science (CPCI-S)en_US
dc.description.wosidWOS:000337926700099


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