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

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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Bibliographic Details
Main Authors: 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
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Autoencoder
convolutional neural networks (CNN)
ECG
signal denoising
LSTM
Online Access:https://ieeexplore.ieee.org/document/10925413/
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