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Polysomnography (PSG) is the gold standard for diagnosing sleep obstructive apnea (OSA). It allows monitoring of breathing events throughout the night. The detection of these events is usually done by trained sleep experts. However, this…

Signal Processing · Electrical Eng. & Systems 2019-06-25 Valentin Thorey , Albert Bou Hernandez , Pierrick J. Arnal , Emmanuel H. During

Obstructive sleep apnea (OSA) is a common sleep disorder caused by abnormal breathing. The severity of OSA can lead to many symptoms such as sudden cardiac death (SCD). Polysomnography (PSG) is a gold standard for OSA diagnosis. It records…

Signal Processing · Electrical Eng. & Systems 2020-07-28 Nannapas Banluesombatkul , Thanawin Rakthanmanon , Theerawit Wilaiprasitporn

Detecting obstructive sleep apnea (OSA) is essential for diagnosing and managing sleep health. Traditionally, this involves clinical settings with hardly accessible processes. We propose that the automated detection of OSA events is…

Snoring is one of the most prominent symptoms of Obstructive Sleep Apnea-Hypopnea Syndrome (OSAH), a highly prevalent disease that causes repetitive collapse and cessation of the upper airway. Thus, accurate snore sound monitoring and…

Sound · Computer Science 2023-01-31 Shenghao Li , Jagmohan Chauhan

Obstructive Sleep Apnea Syndrome (OSAS) is the most common sleep-related breathing disorder. It is caused by an increased upper airway resistance during sleep, which determines episodes of partial or complete interruption of airflow. The…

Machine Learning · Computer Science 2023-02-13 Andrea Bernardini , Andrea Brunello , Gian Luigi Gigli , Angelo Montanari , Nicola Saccomanno

Obstructive sleep apnea (OSA) is one of the most widespread respiratory diseases today. Complete or relative breathing cessations due to upper airway subsidence during sleep is OSA. It has confirmed potential influence on Covid-19…

Machine Learning · Computer Science 2021-12-20 Hosna Ghandeharioun

Study Objectives: To evaluate the agreement between the millimeter-wave radar-based device and polysomnography (PSG) in diagnosis of obstructive sleep apnea (OSA) and classification of sleep stage in children. Methods: 281 children, aged 1…

Signal Processing · Electrical Eng. & Systems 2024-10-02 Wei Wang , Ruobing Song , Yunxiao Wu , Li Zheng , Wenyu Zhang , Zhaoxi Chen , Gang Li , Zhifei Xu

Objective: Sleep related respiratory abnormalities are typically detected using polysomnography. There is a need in general medicine and critical care for a more convenient method to automatically detect sleep apnea from a simple,…

This study proposes a novel lightweight neural network model leveraging features extracted from electrocardiogram (ECG) and respiratory signals for early OSA screening. ECG signals are used to generate feature spectrograms to predict sleep…

Machine Learning · Computer Science 2025-01-06 Hui Pan , Yanxuan Yu , Jilun Ye , Xu Zhang

Obstructive Sleep Apnea (OSA) is a breathing disorder during sleep that affects millions of people worldwide. The diagnosis of OSA often occurs through an overnight polysomnogram (PSG) sleep study that generates a massive amount of…

Applications · Statistics 2026-02-02 Glenn Palmer , Narat Srivali , David B. Dunson

Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) is a sleep-related breathing disorder associated with significant morbidity and mortality worldwide. The gold standard for OSAHS diagnosis, polysomnography (PSG), faces challenges in…

Signal Processing · Electrical Eng. & Systems 2025-04-28 Wei Wang , Chenyang Li , Zhaoxi Chen , Wenyu Zhang , Zetao Wang , Xi Guo , Jian Guan , Gang Li

Sleep apnea is a serious and severely under-diagnosed sleep-related respiration disorder characterized by repeated disrupted breathing events during sleep. It is diagnosed via polysomnography which is an expensive test conducted in a sleep…

Obstructive sleep apnoea (OSA) is a prevalent condition with significant health consequences, yet many patients remain undiagnosed due to the complexity and cost of over-night polysomnography. Acoustic-based screening provides a scalable…

Sound · Computer Science 2026-02-03 Xiaolei Xu , Chaoyue Niu , Guy J. Brown , Hector Romero , Ning Ma

Objective: The aim of the study is to develop a novel method for improved diagnosis of obstructive sleep apnea-hypopnea syndrome (OSAHS) in clinical or home settings, with the focus on achieving diagnostic performance comparable to the…

Signal Processing · Electrical Eng. & Systems 2025-01-28 Wei Wang , Zhaoxi Chen , Wenyu Zhang , Zetao Wang , Xiang Zhao , Chenyang Li , Jian Guan , Shankai Yin , Gang Li

Obstructive sleep apnea (OSA) is believed to contribute significantly to atrial fibrillation (AF) development in certain patients. Recent studies indicate a rising risk of AF with increasing OSA severity. However, the commonly used…

The gold standard to assess respiration during sleep is polysomnography; a technique that is burdensome, expensive (both in analysis time and measurement costs), and difficult to repeat. Automation of respiratory analysis can improve test…

In this study, the development of an automatic algorithm is presented to classify the nocturnal audio recording of an obstructive sleep apnoea (OSA) patient as OSA related snore, simple snore and other sounds. Recent studies has been shown…

Audio and Speech Processing · Electrical Eng. & Systems 2021-03-03 Arun Sebastian , Peter A. Cistulli , Gary Cohen , Philip de Chazal

The obstructive sleep apnea-hypopnea (OSAH) syndrome is a very common and frequently undiagnosed sleep disorder. It is characterized by repeated events of partial (hypopnea) or total (apnea) obstruction of the upper airway while sleeping.…

Signal Processing · Electrical Eng. & Systems 2020-03-25 R. E. Rolon , I. E. Gareis , L. D. Larrateguy , L. E. Di Persia , R. D. Spies , H. L. Rufiner

Sleep apnea (SA) is a chronic sleep-related disorder consisting of repetitive pauses or restrictions in airflow during sleep and is known to be a risk factor for cerebro- and cardiovascular disease. It is generally diagnosed using…

Objective: The aim of this study is to develop an automated classification algorithm for polysomnography (PSG) recordings to detect non-apneic and non-hypopneic arousals. Our particular focus is on detecting the respiratory effort-related…

Signal Processing · Electrical Eng. & Systems 2019-09-09 Ali Bahrami Rad , Morteza Zabihi , Zheng Zhao , Moncef Gabbouj , Aggelos K. Katsaggelos , Simo Särkkä
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