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Authors: Utkars Jain 1 ; Adam Butchy 1 ; Michael Leasure 1 ; Veronica Covalesky 2 ; 3 ; Daniel McCormick 2 ; 3 and Gary Mintz 4

Affiliations: 1 Heart Input Output Inc., 128 N. Craig Street, Suite 406, Pittsburgh, U.S.A. ; 2 Cardiology Consultants of Philadelphia, Philadelphia, Pennsylvania, U.S.A. ; 3 Jefferson University Hospital, Philadelphia, Pennsylvania, U.S.A. ; 4 The Cardiovascular Research Foundation, New York, New York, U.S.A.

Keyword(s): Statistics, ECGs, Cardiac, Correlation.

Abstract: ECGs are a common diagnostic method for diagnosing cardiac pathologies. In this study, the Pearson correlation coefficient is used to examine the latent linear correlations between the leads of a standard 12-lead ECG. We utilize both the original ECG signals from the PTB-XL database and the reconstructed signal generated by a deep learning model, ECGio. We find that leads III, aVL, V1, and V2 are, on average, the leads with the most unique information due to their low correlation with other leads.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Jain, U.; Butchy, A.; Leasure, M.; Covalesky, V.; McCormick, D. and Mintz, G. (2023). Redundancy and Novelty Between ECG Leads Based on Linear Correlation. In Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - BIOSIGNALS; ISBN 978-989-758-631-6; ISSN 2184-4305, SciTePress, pages 359-365. DOI: 10.5220/0011815700003414

@conference{biosignals23,
author={Utkars Jain. and Adam Butchy. and Michael Leasure. and Veronica Covalesky. and Daniel McCormick. and Gary Mintz.},
title={Redundancy and Novelty Between ECG Leads Based on Linear Correlation},
booktitle={Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - BIOSIGNALS},
year={2023},
pages={359-365},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011815700003414},
isbn={978-989-758-631-6},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - BIOSIGNALS
TI - Redundancy and Novelty Between ECG Leads Based on Linear Correlation
SN - 978-989-758-631-6
IS - 2184-4305
AU - Jain, U.
AU - Butchy, A.
AU - Leasure, M.
AU - Covalesky, V.
AU - McCormick, D.
AU - Mintz, G.
PY - 2023
SP - 359
EP - 365
DO - 10.5220/0011815700003414
PB - SciTePress