A novel approach for denoising electrocardiogram signals to detect cardiovascular diseases using an efficient hybrid scheme

P Bing, W Liu, Z Zhai, J Li, Z Guo, Y **
PG Malghan, MK Hota - Biomedical Signal Processing and Control, 2022 - Elsevier
The removal of unwanted noise from electrocardiogram (ECG) recordings is a difficult
procedure in biomedical signal analysis. It alters the signal and affects the accurate …

Atrial fibrillation prediction from critically ill sepsis patients

SK Bashar, EY Ding, AJ Walkey, DD McManus… - Biosensors, 2021 - mdpi.com
Sepsis is defined by life-threatening organ dysfunction during infection and is the leading
cause of death in hospitals. During sepsis, there is a high risk that new onset of atrial …

A deep convolutional autoencoder for automatic motion artifact removal in electrodermal activity

MB Hossain, HF Posada-Quintero… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Objective: This study aimed to develop a robust and data driven automatic motion artifacts
(MA) removal technique from electrodermal activity (EDA) signal. Methods: we proposed a …

[HTML][HTML] Preprocessing and Denoising Techniques for Electrocardiography and Magnetocardiography: A Review

Y Jia, H Pei, J Liang, Y Zhou, Y Yang, Y Cui… - …, 2024 - pmc.ncbi.nlm.nih.gov
This review systematically analyzes the latest advancements in preprocessing techniques
for Electrocardiography (ECG) and Magnetocardiography (MCG) signals over the past …