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Authors: Abdullah Biran 1 and Aleksandar Jeremic 2

Affiliations: 1 Department of Biomedical Engineering, McMaster University, Hamilton, Canada ; 2 Department of Electrical Engineering, McMaster University, Hamilton, Canada

Keyword(s): Biomedical Signal Processing, Biometrics, Electrocardiogram, QRS Segmentation, Short Time Fourier Transform.

Abstract: Human identification from the biological signal the Electrocardiogram (ECG) has been demonstrated in several studies. In this paper, we present a new technique for personal identification using short time Fourier transform (STFT) and histograms of four fiducial QRS features. We examined the applicability of our methodology on 162 ECG records of 81 subjects from the publicly available ECG ID data base. Our experiments show that the normalized Euclidean STFT distance can identify individuals with 95 % accuracy. Hence, with fusing six histogram distances computed from the QRS fiducial features and applying majority voting, the identification accuracy increases up to 100 %. These findings indicate that ECG is sufficiently unique signal and can be useful as biometric identifier.

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Paper citation in several formats:
Biran, A. and Jeremic, A. (2020). ECG based Human Identification using Short Time Fourier Transform and Histograms of Fiducial QRS Features. In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - BIOSIGNALS; ISBN 978-989-758-398-8; ISSN 2184-4305, SciTePress, pages 324-329. DOI: 10.5220/0009168303240329

@conference{biosignals20,
author={Abdullah Biran. and Aleksandar Jeremic.},
title={ECG based Human Identification using Short Time Fourier Transform and Histograms of Fiducial QRS Features},
booktitle={Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - BIOSIGNALS},
year={2020},
pages={324-329},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009168303240329},
isbn={978-989-758-398-8},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - BIOSIGNALS
TI - ECG based Human Identification using Short Time Fourier Transform and Histograms of Fiducial QRS Features
SN - 978-989-758-398-8
IS - 2184-4305
AU - Biran, A.
AU - Jeremic, A.
PY - 2020
SP - 324
EP - 329
DO - 10.5220/0009168303240329
PB - SciTePress

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