Convolutional Autoencoder With Sequential and Channel Attention for Robust ECG Signal Denoising With Edge Device Implementation

Electrocardiograms (ECG) are vital for diagnosing various cardiac conditions but are often corrupted by noise from multiple sources, which can hinder accurate interpretation. Denoising ECG signals is particularly challenging because noise usually overlaps with the frequency range of the signal of in...

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Detalhes bibliográficos

Principais autores:	Alif Wicaksana Ramadhan, Syifa Kushirayati, Salsabila Aurellia, Mgs M. Luthfi Ramadhan, Muhammad Hannan Hunafa, Muhammad Febrian Rachmadi, Aprinaldi Jasa Mantau, Siti Nurmaini, Satria Mandala, Wisnu Jatmiko
Formato:	Artigo
Idioma:	Inglês
Publicado em:	IEEE 2025-01-01
Colecção:	IEEE Access
Assuntos:	Autoencoder convolutional neural networks (CNN) ECG signal denoising LSTM
Acesso em linha:	https://ieeexplore.ieee.org/document/10925413/
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