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 sleeping. This reduction in …

[Retracted] A Comprehensive Review: Computational Models for Obstructive Sleep Apnea Detection in Biomedical Applications

ES JeyaJothi, J Anitha, S Rani… - BioMed research …, 2022 - Wiley Online Library
Obstructive sleep apnea (OSA) is a sleep disorder characterized by periodic episodes of
partial or complete upper airway obstruction caused by narrowing or collapse of the …

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 …

Application of artificial intelligence in the diagnosis of sleep apnea

G Bazoukis, SC Bollepalli, CT Chung, X Li… - Journal of Clinical …, 2023 - jcsm.aasm.org
Study Objectives: Machine learning (ML) models have been employed in the setting of sleep
disorders. This review aims to summarize the existing data about the role of ML techniques …

ApneaNet: A hybrid 1DCNN-LSTM architecture for detection of Obstructive Sleep Apnea using digitized ECG signals

G Srivastava, A Chauhan, N Kargeti, N Pradhan… - … Signal Processing and …, 2023 - Elsevier
Abstract Obstructive Sleep Apnea is a respiratory disorder that can be the origin of fatal heart
and neurological health concerns if left untreated. Despite the availability of diagnosis …

Obstructive sleep apnea prediction from electrocardiogram scalograms and spectrograms using convolutional neural networks

H Nasifoglu, O Erogul - Physiological Measurement, 2021 - iopscience.iop.org
Objective. In this study, we conducted a comparative analysis of deep convolutional neural
network (CNN) models in predicting obstructive sleep apnea (OSA) using …

Deep learning model of sleep EEG signal by using bidirectional recurrent neural network encoding and decoding

Z Fu, C Huang, L Zhang, S Wang, Y Zhang - Electronics, 2022 - mdpi.com
Electroencephalogram (EEG) is a signal commonly used for detecting brain activity and
diagnosing sleep disorders. Manual sleep stage scoring is a time-consuming task, and …

A systematic review of deep learning methods for modeling electrocardiograms during sleep

C Sun, S Hong, J Wang, X Dong… - Physiological …, 2022 - iopscience.iop.org
Sleep is one of the most important human physiological activities, and plays an essential
role in human health. Polysomnography (PSG) is the gold standard for measuring sleep …

[HTML][HTML] ECG-based convolutional neural network in pediatric obstructive sleep apnea diagnosis

C García-Vicente, GC Gutiérrez-Tobal… - Computers in Biology …, 2023 - Elsevier
Obstructive sleep apnea (OSA) is a prevalent respiratory condition in children and is
characterized by partial or complete obstruction of the upper airway during sleep. The …

Systematic review of automated sleep apnea detection based on physiological signal data using deep learning algorithm: a meta-analysis approach

PK Tyagi, D Agarwal - Biomedical Engineering Letters, 2023 - Springer
Sleep apnea (SLA) is a respiratory-related sleep disorder that affects a major proportion of
the population. The gold standard in sleep testing, polysomnography, is costly, inconvenient …