Deep learning in physiological signal data: A survey
Deep Learning (DL), a successful promising approach for discriminative and generative
tasks, has recently proved its high potential in 2D medical imaging analysis; however …
tasks, has recently proved its high potential in 2D medical imaging analysis; however …
A review of automated sleep disorder detection
Automated sleep disorder detection is challenging because physiological symptoms can
vary widely. These variations make it difficult to create effective sleep disorder detection …
vary widely. These variations make it difficult to create effective sleep disorder detection …
Multiscale deep neural network for obstructive sleep apnea detection using RR interval from single-lead ECG signal
Q Shen, H Qin, K Wei, G Liu - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The detection of obstructive sleep apnea (OSA) based on single-lead electrocardiogram
(ECG) is better suited to the noninvasive needs and hardware conditions of wearable mobile …
(ECG) is better suited to the noninvasive needs and hardware conditions of wearable mobile …
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 …
via polysomnography (PSG). However, this method is expensive, time-consuming, and …
Heart rate variability for medical decision support systems: A review
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 …
rhythm is modulated by a wide range of physiological processes. This statement embodies …
Accurate detection of sleep apnea with long short-term memory network based on RR interval signals
Sleep apnea is a common condition that is characterized by sleep-disordered breathing.
Worldwide the number of apnea cases has increased and there has been a growing number …
Worldwide the number of apnea cases has increased and there has been a growing number …
Detection of sleep apnea using Machine learning algorithms based on ECG Signals: A comprehensive systematic review
Sleep apnea (SA) is a common sleep disorder that is not easy to detect. Recent studies have
highlighted ECG analysis as an effective method of diagnosing SA. Because the changes …
highlighted ECG analysis as an effective method of diagnosing SA. Because the changes …
Multitask residual shrinkage convolutional neural network for sleep apnea detection based on wearable bracelet photoplethysmography
Q Shen, X Yang, L Zou, K Wei… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
Sleep apnea syndrome (SAS) is a common chronic respiratory disorder, which seriously
harms human health. In order to realize the large-scale promotion of SAS detection, the SAS …
harms human health. In order to realize the large-scale promotion of SAS detection, the SAS …
Detection of abnormal respiratory events with single channel ECG and hybrid machine learning model in patients with obstructive sleep apnea
Respiratory scoring is an important step in the diagnosis of Obstructive Sleep Apnea (OSA).
Airflow, abdolmel-thorax and pulse oximetry signals are obtained with the help of …
Airflow, abdolmel-thorax and pulse oximetry signals are obtained with the help of …
[HTML][HTML] Automatic detection of obstructive sleep apnea events using a deep CNN-LSTM model
J Zhang, Z Tang, J Gao, L Lin, Z Liu, H Wu… - Computational …, 2021 - hindawi.com
Obstructive sleep apnea (OSA) is a common sleep-related respiratory disorder. Around the
world, more and more people are suffering from OSA. Because of the limitation of monitor …
world, more and more people are suffering from OSA. Because of the limitation of monitor …