REVIEW

ECG-based biometric identification: some modern approaches

Astapov AA1, Davydov DV2, Egorov AI1, Drozdov DV2, Glukhovskij EM1
About authors

1 Laboratory of Medical Instrumentation Engineering,
Moscow Institute of Physics and Technology (State University), Dolgoprudny, Moscow oblast, Russia

2 OOO Altomedika, Moscow, Russia

Correspondence should be addressed: Artem Astapov
Institutskiy per. 9, str. 7, Dolgoprudny, Moskovskaya oblast, Russia, 141700; ude.hcetsyhp@vopatsa.metra

Received: 2015-12-07 Accepted: 2015-12-31 Published online: 2017-01-05
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The uniqueness of electrical activity of every human heart prompts us to use the ECG as a biometric parameter in various security and authentication systems as it is easy and cheap to extract the signal and difficult to fake it or obtain nonconsensually. At the moment various approaches to researching a possibility of human identification by ECG are used. Identification mode includes the following stages: data collection, procession, feature extraction, classification. Researchers use different mathematical algorithms at every stage: principal component analysis, wavelets, neural networks, etc. This article reviews the most significant studies of ECG based human identification and compares their results and accuracy of conceptual approaches.

Keywords: classification, ECG, identification, biometrics

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