ECG Signal Classification Using Interpretable KAN: Towards Predictive Diagnosis of Arrhythmias

ECG Signal Classification Using Interpretable KAN: Towards Predictive Diagnosis of Arrhythmias

To address the need for accurate classification of electrocardiogram (ECG) signals, we employ an interpretable KAN to classify arrhythmia diseases. Experimental evaluation of the MIT-BIH and PTB datasets demonstrates the significant superiority of the KAN in classifying arrhythmia diseases. Specific...

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Bibliographic Details
Main Authors: Hongzhen Cui, Shenhui Ning, Shichao Wang, Wei Zhang, Yunfeng Peng
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Algorithms
Subjects:
ECG signal
KAN
arrhythmia
balance
variance sorting
Online Access:https://www.mdpi.com/1999-4893/18/2/90

Internet

https://www.mdpi.com/1999-4893/18/2/90

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