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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, Feature Lags.

Abstract: In this paper, we present a new segmented based method for human identification using Fréchet distances and the characteristics of the lag-feature matrices of six fiducial based QRS features. We examined the applicability of our methodology on 124 ECG records of 62 subjects from the publicly available ECG ID data base. Our experiments show that the Fréchet distance can identify majority of the subjects (44 individuals) using the feature matrix of QRS segment lagged by one beat with an identification accuracy ranging from 80% to 100%. Our preliminary results indicate that identifying humans using segmented approaches can be potentially useful.

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Paper citation in several formats:
Biran, A. and Jeremic, A. (2021). Segmented ECG Bio Identification using Fréchet Mean Distance and Feature Matrices of Fiducial QRS Features. In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - BIOSIGNALS; ISBN 978-989-758-490-9; ISSN 2184-4305, SciTePress, pages 223-227. DOI: 10.5220/0010262300002865

@conference{biosignals21,
author={Abdullah Biran. and Aleksandar Jeremic.},
title={Segmented ECG Bio Identification using Fréchet Mean Distance and Feature Matrices of Fiducial QRS Features},
booktitle={Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - BIOSIGNALS},
year={2021},
pages={223-227},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010262300002865},
isbn={978-989-758-490-9},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - BIOSIGNALS
TI - Segmented ECG Bio Identification using Fréchet Mean Distance and Feature Matrices of Fiducial QRS Features
SN - 978-989-758-490-9
IS - 2184-4305
AU - Biran, A.
AU - Jeremic, A.
PY - 2021
SP - 223
EP - 227
DO - 10.5220/0010262300002865
PB - SciTePress

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