Implementation of a Capsule Network Algorithm for ECG Signal Classification in Arrhythmia Detection

DOI

10.2991/978-94-6463-998-8_24How to use a DOI?

Keywords

Arrhythmia; ECG; CapsNet

Abstract

Cardiovascular diseases remain one of the primary contributors to global mortality rates. Insufficient early diagnostic tools and the limited availability of cardiology experts pose challenges to accurate arrhythmia identification, which may elevate the likelihood of severe complications and fatal outcomes. This study applies the Capsule Network (CapsNet) model to categorize ECG signal patterns associated with arrhythmic conditions. CapsNet demonstrates a strong capability in capturing intricate spatial relationships within sequential physiological data, including cardiac waveforms. By maintaining spatial hierarchies and dependencies between features, CapsNet effectively identifies subtle morphological variations in cardiac waveforms. The data in this study were obtained through electrocardiogram (ECG) recordings of subjects grouped into three activity categories: sitting, walking, and running. The acquired ECG datasets were subsequently utilized to train and evaluate the classification model for detecting potential arrhythmic events from observed cardiac activity patterns. The CapsNet algorithm achieved an accuracy rate of up to 91% in the classification process. The findings suggest that the CapsNet framework could serve as an effective approach for the early identification of arrhythmias.

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  - Erick Hartanto
AU  - Frederick Anderson
AU  - Joverio Nerkotan
AU  - Delima Sitanggang
AU  - Mardi Turnip
PY  - 2026
DA  - 2026/03/05
TI  - Implementation of a Capsule Network Algorithm for ECG Signal Classification in Arrhythmia Detection
BT  - Proceedings of the 1st International Conference of Technology, Innovation, Design & Enterprise (ICTIDE 2025)
PB  - Atlantis Press
SP  - 196
EP  - 211
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-998-8_24
DO  - 10.2991/978-94-6463-998-8_24
ID  - Hartanto2026
ER  -