A novel human identification system based on electrocardiogram features
dc.authorid | 0000-0002-7008-4778 | |
dc.authorid | 0000-0002-4597-0954 | |
dc.authorid | 0000-0003-1562-5524 | |
dc.contributor.author | Gürkan, Hakan | en_US |
dc.contributor.author | Güz, Ümit | en_US |
dc.contributor.author | Yarman, Bekir Sıddık Binboğa | en_US |
dc.date.accessioned | 2015-07-14T23:46:48Z | |
dc.date.available | 2015-07-14T23:46:48Z | |
dc.date.issued | 2013 | |
dc.department | Işık Üniversitesi, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü | en_US |
dc.department | Işık University, Faculty of Engineering, Department of Electrical-Electronics Engineering | en_US |
dc.description | The work is supported by The Scientific Research Fund of ISIK University (Project Number: 10A301) | en_US |
dc.description.abstract | In 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.description.version | Publisher's Version | en_US |
dc.identifier.citation | Gürkan, 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.2013.6651266 | en_US |
dc.identifier.doi | 10.1109/ISSCS.2013.6651266 | |
dc.identifier.endpage | 4 | |
dc.identifier.isbn | 9781467361415 | |
dc.identifier.isbn | 9781479931934 | |
dc.identifier.isbn | 9781467361439 | |
dc.identifier.scopus | 2-s2.0-84890886583 | |
dc.identifier.scopusquality | N/A | |
dc.identifier.startpage | 1 | |
dc.identifier.uri | https://hdl.handle.net/11729/599 | |
dc.identifier.uri | http://dx.doi.org/10.1109/ISSCS.2013.6651266 | |
dc.identifier.wos | WOS:000337926700099 | |
dc.identifier.wosquality | N/A | |
dc.indekslendigikaynak | Web of Science | en_US |
dc.indekslendigikaynak | Scopus | en_US |
dc.indekslendigikaynak | Conference Proceedings Citation Index – Science (CPCI-S) | en_US |
dc.institutionauthor | Gürkan, Hakan | en_US |
dc.institutionauthor | Güz, Ümit | en_US |
dc.institutionauthorid | 0000-0002-7008-4778 | |
dc.institutionauthorid | 0000-0002-4597-0954 | |
dc.language.iso | en | en_US |
dc.peerreviewed | Yes | en_US |
dc.publicationstatus | Published | en_US |
dc.publisher | IEEE | en_US |
dc.relation.ispartof | International Symposium on Signals, Circuits and Systems ISSCS2013 | en_US |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | ECG | en_US |
dc.subject | Human identification | en_US |
dc.subject | Feature extraction | en_US |
dc.subject | Authentication | en_US |
dc.subject | Band-pass filters | en_US |
dc.subject | Databases | en_US |
dc.subject | Discrete cosine transforms | en_US |
dc.subject | Electrocardiography | en_US |
dc.subject | Mel frequency cepstral coefficient | en_US |
dc.subject | AC-DCT feature extraction | en_US |
dc.subject | ACDCT based biometric authentication system | en_US |
dc.subject | ECG signal | en_US |
dc.subject | MFCC based biometric authentication system | en_US |
dc.subject | MFCC feature extraction | en_US |
dc.subject | PTB database | en_US |
dc.subject | QRS beat information | en_US |
dc.subject | Average frame recognition rate | en_US |
dc.subject | Biometric authentication approach | en_US |
dc.subject | Electrocardiogram feature extraction | en_US |
dc.subject | Human identification system | en_US |
dc.subject | Bioelectric potentials | en_US |
dc.subject | Cryptographic protocols | en_US |
dc.subject | Medical signal detection | en_US |
dc.subject | Medical signal processing | en_US |
dc.title | A novel human identification system based on electrocardiogram features | en_US |
dc.type | Conference Object | en_US |
dspace.entity.type | Publication |
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