Research on ECG Signal Classification Based on Hybrid Residual Network

Research on ECG Signal Classification Based on Hybrid Residual Network

Arrhythmia detection in electrocardiogram (ECG) signals is essential for monitoring cardiovascular health. Current automated arrhythmia classification methods frequently encounter difficulties in detecting multiple cardiac abnormalities, particularly when dealing with imbalanced datasets. This paper...

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Bibliographic Details
Main Authors: Tianyu Qi, He Zhang, Huijun Zhao, Chong Shen, Xiaochen Liu
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Applied Sciences
Subjects:
electrocardiogram (ECG)
hybrid residual network (Hybrid ResNet)
depthwise separable convolution
data preprocessing
arrhythmia classification
Online Access:https://www.mdpi.com/2076-3417/14/23/11202
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