Arrhythmia Identification Based On ECG Signal Analysis Using The Birch Algorithm

DOI

10.2991/978-94-6463-998-8_23How to use a DOI?

Keywords

Electrocardiogram (ECG); Arrhythmia Detection; BIRCH Algorithm; Unsupervised Learning; Cardiovascular Disease

Abstract

Cardiovascular diseases remain the primary cause of mortality worldwide. Limited access to early detection technology and the shortage of medical experts make diagnosis and treatment both costly and less effective. The absence of accurate diagnostic methods often leads to late detection of abnormal heart rhythms, increasing the risk of severe complications. This study presents an approach for classifying electrocardiogram signals to identify potential irregularities in heart rhythm using a clustering algorithm known as Balanced Iterative Reducing and Clustering using Hierarchies. The algorithm was selected for its efficiency in handling large and complex signal datasets while maintaining accurate pattern grouping. Electrocardiogram signals were collected from subjects under various physiological conditions and processed through several stages, including preprocessing, feature extraction, and clustering. The results demonstrate that the proposed method can effectively differentiate normal and irregular heartbeat patterns with high accuracy. This finding highlights the potential of the algorithm as a reliable and efficient tool for early and automatic detection of heart rhythm disorders.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Sherlin Sonali Kaur
AU  - Kenzy Yapimin
AU  - Darvin Wijaya Sinaga
AU  - Jennifer Cenora
AU  - Delima Sitanggang
AU  - Mardi Turnip
PY  - 2026
DA  - 2026/03/05
TI  - Arrhythmia Identification Based On ECG Signal Analysis Using The Birch Algorithm
BT  - Proceedings of the 1st International Conference of Technology, Innovation, Design & Enterprise (ICTIDE 2025)
PB  - Atlantis Press
SP  - 179
EP  - 195
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-998-8_23
DO  - 10.2991/978-94-6463-998-8_23
ID  - Kaur2026
ER  -