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Automated ECG arrhythmia classification using hybrid CNN-SVM architectures

Amine Ben Slama Yessine Amri Ahmed Fnaiech Hanene Sahli

Journal of Electronic Science and Technology2025，Vol.23Issue(3)：P.43-55,13.

Journal of Electronic Science and Technology2025，Vol.23Issue(3)：P.43-55,13.DOI:10.1016/j.jnlest.2025.100316

Automated ECG arrhythmia classification using hybrid CNN-SVM architectures

Amine Ben Slama ¹Yessine Amri ²Ahmed Fnaiech ³Hanene Sahli³

作者信息

1. Higher Institute of Medical Technologies of Tunis,University of Tunis El Manar,Tunis,1006,Tunisia
2. Biochemistry Laboratory,Bechir Hamza Children’s Hospital,Tunis,1007,Tunisia Higher Institute of Applied Studies in Humanity Le Kef,University of Jendouba,Le Kef,7001,Tunisia
3. National Higher School of Engineers of Tunis,University of Tunis,Tunis,1008,Tunisia
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摘要

关键词

Arrhythmia/Classification/Convolutional neural networks/ECG signals/Support vector machine

分类

医药卫生

引用本文复制引用

Amine Ben Slama,Yessine Amri,Ahmed Fnaiech,Hanene Sahli..Automated ECG arrhythmia classification using hybrid CNN-SVM architectures[J].Journal of Electronic Science and Technology,2025,23(3):P.43-55,13.

Journal of Electronic Science and Technology

ISSN：1674-862X

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