[HTML][HTML] A systematic review of detecting sleep apnea using deep learning

SS Mostafa, F Mendonça, A G. Ravelo-García… - Sensors, 2019 - mdpi.com
Sleep apnea is a sleep related disorder that significantly affects the population.
Polysomnography, the gold standard, is expensive, inaccessible, uncomfortable and an …

[HTML][HTML] A survey on recent advances in machine learning based sleep apnea detection systems

A Ramachandran, A Karuppiah - Healthcare, 2021 - mdpi.com
Sleep apnea is a sleep disorder that affects a large population. This disorder can cause or
augment the exposure to cardiovascular dysfunction, stroke, diabetes, and poor productivity …

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 …

Automated sleep apnea detection in raw respiratory signals using long short-term memory neural networks

T Van Steenkiste, W Groenendaal… - IEEE journal of …, 2018 - ieeexplore.ieee.org
Sleep apnea is one of the most common sleep disorders and the consequences of
undiagnosed sleep apnea can be very severe, ranging from increased blood pressure to …

Classification of Obstructive Sleep Apnoea from single-lead ECG signals using convolutional neural and Long Short Term Memory networks

H Almutairi, GM Hassan, A Datta - Biomedical Signal Processing and …, 2021 - Elsevier
Abstract Obstructive Sleep Apnoea (OSA) is a breathing disorder that happens during sleep.
Polysomnography (PSG) is typically used as a reference standard for the diagnosis of OSA …

Automatic detection of sleep apnea from single-lead ECG signal using enhanced-deep belief network model

PK Tyagi, D Agrawal - Biomedical Signal Processing and Control, 2023 - Elsevier
Sleep apnea (SLA) is a commonly reported sleep disorder that is characterized by frequent
breathing interruptions during sleep. In recent years, various approaches have been made …

Single sensor techniques for sleep apnea diagnosis using deep learning

RK Pathinarupothi, ES Rangan… - 2017 IEEE …, 2017 - ieeexplore.ieee.org
A large number of obstructive sleep apnea (OSA) cases are under-diagnosed due
unavailability, inconvenience or expense of sleep labs. Hence, an automated detection by …

Automatic system for obstructive sleep apnea events detection using convolutional neural network

L Cen, ZL Yu, T Kluge, W Ser - 2018 40th annual international …, 2018 - ieeexplore.ieee.org
Obstructive Sleep Apnea (OSA) is characterized by repetitive episodes of airflow reduction
(hypopnea) or cessation (apnea), which, as a prevalent sleep disorder, can cause people to …

Energy-efficient FPGA based sleep apnea detection using EEG signals

MS Alam, Y Siddiqui, M Hasan, O Farooq… - IEEE Access, 2024 - ieeexplore.ieee.org
Sleep apnea is a prevalent sleep disorder characterized by frequent interruptions in
breathing during sleep, leading to decreased levels of blood oxygen. This research …

[HTML][HTML] Portable sleep apnea syndrome screening and event detection using long short-term memory recurrent neural network

HC Chang, HT Wu, PC Huang, HP Ma, YL Lo… - Sensors, 2020 - mdpi.com
Obstructive sleep apnea/hypopnea syndrome (OSAHS) is characterized by repeated airflow
partial reduction or complete cessation due to upper airway collapse during sleep. OSAHS …