Unsupervised Motif and Discord Discovery in ECG

Lucas Peres, Livia Almada Cruz, Ticiana Coelho da Silva, Regis Pires Magalhães, João Paulo Madeiro, José Macêdo

2025

Abstract

Cardiovascular disease stands as the leading global cause of morbidity and mortality. Electrocardiograms (ECGs) are among the most effective tools for detecting arrhythmia and other cardiovascular diseases, as well as other applications like emotion recognition and stress level stratification. The ECG-based diagnostic relies on specialized physicians to manually explore the whole signal. This paper presents an unsupervised solution for ECG analysis, obviating specialists’ need to manually run over the entire dataset to identify representative segments (motifs) or non-repeated patterns (discords). The method was experimented with an open dataset and showed promising results.

Paper Citation

in Harvard Style

Peres L., Cruz L., Coelho da Silva T., Magalhães R., Madeiro J. and Macêdo J. (2025). Unsupervised Motif and Discord Discovery in ECG. In Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-749-8, SciTePress, pages 243-250. DOI: 10.5220/0013287900003929

in Bibtex Style

@conference{iceis25,
author={Lucas Peres and Livia Cruz and Ticiana Coelho da Silva and Regis Magalhães and João Madeiro and José Macêdo},
title={Unsupervised Motif and Discord Discovery in ECG},
booktitle={Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2025},
pages={243-250},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013287900003929},
isbn={978-989-758-749-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Unsupervised Motif and Discord Discovery in ECG
SN - 978-989-758-749-8
AU - Peres L.
AU - Cruz L.
AU - Coelho da Silva T.
AU - Magalhães R.
AU - Madeiro J.
AU - Macêdo J.
PY - 2025
SP - 243
EP - 250
DO - 10.5220/0013287900003929
PB - SciTePress