International Conference on Computer and Knowledge Engineering

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Evaluation of Efficient Electrocardiomatrix-based Identification Using Deep Learning Methods

Authors :

Amirhossein Safari¹ Narges Mokhtari² Mohsen Hooshmand³ Sadegh Sadeghi⁴ Peyman Pahlevani⁵

1- Institute for Advanced Studies in Basic Sciences (IASBS) 2- Shahid Rajaee University 3- Institute for Advanced Studies in Basic Sciences (IASBS) 4- Institute for Advanced Studies in Basic Sciences (IASBS) 5- Institute for Advanced Studies in Basic Sciences (IASBS)

Keywords :

User identification،Biometric systems،ECG،ECM،Deep learning

Abstract :

Nowadays, biometric systems are essential for identification and authentication. This study proposes deep learning models for user identification using electrocardiometrices (ECMs) as input. The proposed models are evaluated from different perspectives to assess their efficiency and performance for user identification. One aspect involves comparing convolutional and recurrent neural models. In contrast, another element consists of testing the models with different numbers of ECMs and beats per frame for generating the ECMs. The results are based on an analysis of three different electrocardiogram datasets.

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