Evaluating the Impact of Windowing Techniques on Fourier Transform-Preprocessed Signals for Deep Learning-Based ECG Classification

Evaluating the Impact of Windowing Techniques on Fourier Transform-Preprocessed Signals for Deep Learning-Based ECG Classification

(1) Background: Arrhythmias, or irregular heart rhythms, are a prevalent cardiovascular condition and are diagnosed using electrocardiogram (ECG) signals. Advances in deep learning have enabled automated analysis of these signals. However, the effectiveness of deep learning models depends greatly on...

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Bibliographic Details
Main Authors: Niken Prasasti Martono, Hayato Ohwada
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Hearts
Subjects:
arrhythmia
electrocardiogram (ECG)
ECG classification
signal processing
deep learning
convolutional neural network (CNN)
Online Access:https://www.mdpi.com/2673-3846/5/4/37
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