ECG Signal Classification Using MODWT and CNN for Early Detection of Cardiac Abnormalities

ECG Signal Classification Using MODWT and CNN for Early Detection of Cardiac Abnormalities

Accurate classification of ECG signals is crucial for the early detection of cardiac abnormalities. This study proposes a method that integrates Maximal Overlap Discrete Wavelet Transform (MODWT) for feature extraction with a Convolutional Neural Network (CNN) to enhance classification performance....

Full description

Saved in:
Bibliographic Details
Main Authors: Mohammad Yusuf Hamadani, Zainul Abidin, Muhammad Fauzan Edy Purnomo
Format: Article
Language:English
Published: Departement of Electrical Engineering, Faculty of Engineering, Universitas Brawijaya 2025-06-01
Series:Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems)
Subjects:
cardiac abnormalities
cnn
ecg signal classification
modwt
qrs complex
Online Access:https://jurnaleeccis.ub.ac.id/index.php/eeccis/article/view/1769
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items