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REPČÍK, T. POLÁKOVÁ, V. WALOSZEK, V. NOHEL, M. SMITAL, L. VÍTEK, M. KOLÁŘ, R.
Originální název
Biometric Authentication Using the Unique Characteristics of the ECG Signal
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
ECG is a biological signal specific for each person that is hard to create artificially. Therefore, its usage in biometry is highly investigated. It may be assumed that in the future, ECG for biometric purposes will be measured by wearable devices. Therefore, the quality of the acquired data will be worse compared to ambulatory ECG. In this study, we proposed and tested three different ECG-based authentication methods on data measured by Maxim Integrated wristband. Specifically, 29 participants were involved. The first method extracted 22 time-domain features – intervals and amplitudes from each heartbeat and Hjorth descriptors of an average heartbeat. The second method used 320 features extracted from the wavelet domain. For both methods a random forest was used as a classifier. The deep learning method was selected as the third method. Specifically, the 1D convolutional neural network with embedded feed-forward neural network was used to classify the raw signal of every heartbeat. The first method reached an average false acceptance rate (FAR) 7.11% and false rejection rate (FRR) 6.49%. The second method reached FAR 6.96% and FRR 21.61%. The third method reached FAR 0.57% and FRR 0.00%.
Klíčová slova
ECG, biometric authentication, Hjorth descriptors, wavelet domain features, 1D convolutional neural network
Autoři
REPČÍK, T.; POLÁKOVÁ, V.; WALOSZEK, V.; NOHEL, M.; SMITAL, L.; VÍTEK, M.; KOLÁŘ, R.
Vydáno
28. 12. 2020
Nakladatel
IEEE
Místo
Rimini, Italy
ISSN
2325-887X
Periodikum
Computing in Cardiology
Ročník
47
Číslo
1
Stát
Spojené státy americké
Strany od
Strany do
4
Strany počet
URL
http://www.cinc.org/archives/2020/pdf/CinC2020-321.pdf
Plný text v Digitální knihovně
http://hdl.handle.net/11012/196702
BibTex
@inproceedings{BUT166055, author="Tomáš {Repčík} and Veronika {Poláková} and Vojtěch {Waloszek} and Michal {Nohel} and Lukáš {Smital} and Martin {Vítek} and Radim {Kolář}", title="Biometric Authentication Using the Unique Characteristics of the ECG Signal", booktitle="Computing in Cardiology 2020", year="2020", journal="Computing in Cardiology", volume="47", number="1", pages="1--4", publisher="IEEE", address="Rimini, Italy", doi="10.22489/CinC.2020.321", issn="2325-887X", url="http://www.cinc.org/archives/2020/pdf/CinC2020-321.pdf" }