A novel deep feature transfer-based OSA detection method using sleep sound signals
J Luo, H Liu, X Gao, B Wang, X Zhu, Y Shi… - Physiological …, 2020 - iopscience.iop.org
Objective: Polysomnography is typically used to evaluate the severity of obstructive sleep
apnea (OSA) but the inconvenience of application and high cost considerably affect the …
apnea (OSA) but the inconvenience of application and high cost considerably affect the …
Convolutional neural network for screening of obstructive sleep apnea using snoring sounds
R Li, W Li, K Yue, Y Li - Biomedical Signal Processing and Control, 2023 - Elsevier
Screening and assessment for obstructive sleep apnea hypopnea syndrome (OSAHS) has
attracted growing attention to improve the life of patients with sleep apnea. The gold …
attracted growing attention to improve the life of patients with sleep apnea. The gold …
Design of embedded real-time system for snoring and OSA detection based on machine learning
H Luo, H Li, Y Lu, X Lin, L Zhou, M Wang - Measurement, 2023 - Elsevier
Obstructive sleep apnea (OSA) is a common sleep disorder. As a gold standard to detect
OSA, the polysomnography (PSG) is widely used. However, the acquisition of nighttime PSG …
OSA, the polysomnography (PSG) is widely used. However, the acquisition of nighttime PSG …
Acoustic screening for obstructive sleep apnea in home environments based on deep neural networks
Obstructive sleep apnea (OSA) is a chronic and prevalent condition with well-established
comorbidities. However, many severe cases remain undiagnosed due to poor access to …
comorbidities. However, many severe cases remain undiagnosed due to poor access to …
SST: a snore shifted-window transformer method for potential obstructive sleep apnea patient diagnosis
Objective. Obstructive sleep apnea (OSA) is a high-incidence disease that is seriously
harmful and potentially dangerous. The objective of this study was to develop a noncontact …
harmful and potentially dangerous. The objective of this study was to develop a noncontact …
Obstructive sleep apnea detection based on sleep sounds via deep learning
B Wang, X Tang, H Ai, Y Li, W Xu… - Nature and Science of …, 2022 - Taylor & Francis
Purpose This study aimed to propose a novel deep-learning method for automatic sleep
apneic event detection and thus to estimate the apnea hypopnea index (AHI) and identify …
apneic event detection and thus to estimate the apnea hypopnea index (AHI) and identify …
Design of real-time system based on machine learning for snoring and osa detection
H Luo, L Zhang, L Zhou, X Lin… - ICASSP 2022-2022 …, 2022 - ieeexplore.ieee.org
Obstructive sleep apnea (OSA) is a common sleep disorder. The diagnosis of OSA based on
snoring is low-cost, convenient and non-invasive. In this study, we place a microphone …
snoring is low-cost, convenient and non-invasive. In this study, we place a microphone …
Obstructive sleep apnea detection using difference in feature and modified minimum distance classifier
The current gold standard of Obstructive Sleep Apnea (OSA) diagnosis involves the use of a
Polysomnography (PSG) system which requires the patient to stay in the hospital for …
Polysomnography (PSG) system which requires the patient to stay in the hospital for …
[HTML][HTML] ECG and SpO2 signal-based real-time sleep apnea detection using feed-forward artificial neural network
Sleep apnea (SA) is a common sleep disorder characterized by respiratory disturbance
during sleep. Polysomnography (PSG) is the gold standard for apnea diagnosis, but it is time …
during sleep. Polysomnography (PSG) is the gold standard for apnea diagnosis, but it is time …
Deep learning of sleep apnea-hypopnea events for accurate classification of obstructive sleep apnea and determination of clinical severity
Abstract Background/Objective: Automatic apnea/hypopnea events classification, crucial for
clinical applications, often faces challenges, particularly in hypopnea detection. This study …
clinical applications, often faces challenges, particularly in hypopnea detection. This study …