A novel biometric identification system based on fingertip electrocardiogram and speech signals

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dc.authorid0000-0002-7008-4778en_US
dc.contributor.authorGuven, Gokhan
dc.contributor.authorGuz, Umit
dc.contributor.authorGürkan, Hakan
dc.date.accessioned2022-08-05T13:28:14Z
dc.date.available2022-08-05T13:28:14Z
dc.date.issued2021en_US
dc.departmentBTÜ, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.description.abstractIn this research work, we propose a one dimensional Convolutional Neural Network (CNN) based biometric identification system that combines speech and ECG modalities. The aim is to find an effective identification strategy while enhancing both the confidence and the performance of the system. In our first approach, we have developed a voting-based ECG and speech fusion system to improve the overall performance compared to the conventional methods. In the second approach, we have developed a robust rejection algorithm to prevent unauthorized access to the fusion system. We also presented a newly developed ECG spike and inconsistent beats removal algorithm to detect and eliminate the problems caused by portable fingertip ECG devices and patient movements. Furthermore, we have achieved a system that can work with only one authorized user by adding a Universal Background Model to our algorithm. In the first approach, the proposed fusion system achieved a 100% accuracy rate for 90 people by taking the average of 3-fold cross-validation. In the second approach, by using 90 people as genuine classes and 26 people as imposter classes, the proposed system achieved 92% accuracy in identiying genuine classes and 96% accuracy in rejecting imposter classes.en_US
dc.identifier.doi10.1016/j.dsp.2021.103306en_US
dc.identifier.issn1051-2004
dc.identifier.issn1095-4333
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12885/2021
dc.identifier.volume121en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.institutionauthorGürkan, Hakan
dc.language.isoenen_US
dc.publisherAcademic Pressen_US
dc.relation.ispartofDIGITAL SIGNAL PROCESSINGen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBiometric identificationen_US
dc.subjectBiometric recognitionen_US
dc.subjectCNNen_US
dc.subjectFingertip ECGen_US
dc.subjectSpeechen_US
dc.titleA novel biometric identification system based on fingertip electrocardiogram and speech signalsen_US
dc.typeArticleen_US

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