Hybrid convolutional neural network-long short-term memory model for automated detection of sleep stages

G Sudhamathy, N Valliammal… - … , IoT and Security …, 2023 - ieeexplore.ieee.org
Sleep is essential to maintain the physical and mental fitness of a living being. An irregular
sleep cycle may cause extreme drowsiness, snoring and sleep interruptions, leading to …

A deep learning model for automated sleep stages classification using PSG signals

O Yildirim, UB Baloglu, UR Acharya - International journal of …, 2019 - mdpi.com
Sleep disorder is a symptom of many neurological diseases that may significantly affect the
quality of daily life. Traditional methods are time-consuming and involve the manual scoring …

A systematic review on deep learning models for sleep stage classification

TR Sri, J Madala, SL Duddukuru… - … on Trends in …, 2022 - ieeexplore.ieee.org
Sleep is a key aspect of the body's recuperation, memory integration and consolidation
processes, as well as a vital part of overall health. Early discovery of sleep related disorders …

Sleep Track: Automated Detection and Classification of Sleep Stages

RPR Kumar, A Rithesh, P Josh, BK Raj… - E3S Web of …, 2023 - e3s-conferences.org
Sleep is vital for our body's physical restoration, but sleep disorders can cause various
problems. Determining sleep stages is essential for diagnosing and curing such disorders …

Detection Sleep Stages Using Deep Learning for Better Sleep Management: Systematic Literature Review

MHS Budi, B Ferdiman, S Sidharta - Procedia Computer Science, 2023 - Elsevier
Sleep is a passive activity that has a major impact on our bodies. Sleep is also a
fundamental necessity in life. Given that in this day and age many changes have occurred …

Sleep disorder and apnea events detection framework with high performance using two-tier learning model design

RS Arslan - PeerJ Computer Science, 2023 - peerj.com
Sleep apnea is defined as a breathing disorder that affects sleep. Early detection of sleep
apnea helps doctors to take intervention for patients to prevent sleep apnea. Manually …

A hierarchical approach for the diagnosis of sleep disorders using convolutional recurrent neural network

A Wadichar, S Murarka, D Shah, A Bhurane… - IEEE …, 2023 - ieeexplore.ieee.org
Sleep is an essential criterion for health. However, sleep disorders degrade the sleep
quality. Hence, to diagnose sleep disorders, sleep monitoring is crucial. The cyclic …

Automated detection of sleep stages using deep learning techniques: A systematic review of the last decade (2010–2020)

HW Loh, CP Ooi, J Vicnesh, SL Oh, O Faust… - Applied Sciences, 2020 - mdpi.com
Sleep is vital for one's general well-being, but it is often neglected, which has led to an
increase in sleep disorders worldwide. Indicators of sleep disorders, such as sleep …

A multimodal attention-fusion convolutional neural network for automatic detection of sleep disorders

W Wang, J Li, Y Fang, Y Zheng, F You - Applied Intelligence, 2024 - Springer
Sleep is essential for human physical and mental health. Sleep disorders are a significant
threat to human health, and a large number of people in the world suffer from sleep …

[PDF][PDF] Deep Learning Analysis for Estimating Sleep Syndrome Detection Utilizing the Twin Convolutional Model FTC2

T Cvetko, T Robek - BOHR Int. J. Internet Things Artif. Intell. Mach …, 2022 - researchgate.net
Sleep specialists often conduct manual sleep stage scoring by visually inspecting the
patient's neurophysiological signals collected at sleep labs. This is a difficult, tedious and a …