A review of automated sleep disorder detection

S Xu, O Faust, S Seoni, S Chakraborty… - Computers in biology …, 2022 - Elsevier
Automated sleep disorder detection is challenging because physiological symptoms can
vary widely. These variations make it difficult to create effective sleep disorder detection …

Heart rate variability for medical decision support systems: A review

O Faust, W Hong, HW Loh, S Xu, RS Tan… - Computers in biology …, 2022 - Elsevier
Abstract Heart Rate Variability (HRV) is a good predictor of human health because the heart
rhythm is modulated by a wide range of physiological processes. This statement embodies …

Sleep apnea detection from single-lead ECG: A comprehensive analysis of machine learning and deep learning algorithms

M Bahrami, M Forouzanfar - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Sleep apnea is a common sleep breathing disorder (SBD) in which patients suffer from
stop** or decreasing airflow to the lungs for more than 10 sec. Accurate detection of sleep …

A deep learning based model using RNN-LSTM for the detection of schizophrenia from EEG data

R Supakar, P Satvaya, P Chakrabarti - Computers in Biology and Medicine, 2022 - Elsevier
Normal life can be ensured for schizophrenic patients if diagnosed early.
Electroencephalogram (EEG) carries information about the brain network connectivity which …

Automated detection of coronary artery disease, myocardial infarction and congestive heart failure using GaborCNN model with ECG signals

V Jahmunah, EYK Ng, TR San, UR Acharya - Computers in biology and …, 2021 - Elsevier
Cardiovascular diseases (CVDs) are main causes of death globally with coronary artery
disease (CAD) being the most important. Timely diagnosis and treatment of CAD is crucial to …

Detection of obstructive sleep apnea from single-channel ECG signals using a CNN-transformer architecture

H Liu, S Cui, X Zhao, F Cong - Biomedical Signal Processing and Control, 2023 - Elsevier
Obstructive sleep apnea (OSA) is a sleep breathing disorder that can seriously affect the
health of patients. The manual diagnostic of OSA through the Polysomnography (PSG) …

Automatic diagnosis of sleep apnea from biomedical signals using artificial intelligence techniques: Methods, challenges, and future works

P Moridian, A Shoeibi, M Khodatars… - … : Data Mining and …, 2022 - Wiley Online Library
Apnea is a sleep disorder that stops or reduces airflow for a short time during sleep. Sleep
apnea may last for a few seconds and happen for many while slee**. This reduction in …

Obstructive sleep apnea detection from single-lead electrocardiogram signals using one-dimensional squeeze-and-excitation residual group network

Q Yang, L Zou, K Wei, G Liu - Computers in biology and medicine, 2022 - Elsevier
Obstructive sleep apnea (OSA), which has high morbidity and complications, is diagnosed
via polysomnography (PSG). However, this method is expensive, time-consuming, and …

Detection of sleep apnea using deep neural networks and single-lead ECG signals

A Zarei, H Beheshti, BM Asl - Biomedical Signal Processing and Control, 2022 - Elsevier
Sleep apnea causes frequent cessation of breathing during sleep. Feature extraction
approaches play a key role in the performance of apnea detection algorithms that use single …

OSACN-Net: Automated classification of sleep apnea using deep learning model and smoothed Gabor spectrograms of ECG signal

K Gupta, V Bajaj, IA Ansari - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Obstructive sleep apnea (OSA) is a severe sleep-associated respiratory disorder, caused
due to periodic disruption of breath during sleep. It may cause a number of serious …