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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…

Sleep apnea is the most common sleep disturbance and it is an important risk factor for cardiovascular disorders. Its detection relies on a polysomnography, a combination of diverse exams. In order to detect changes due to sleep…

医学物理 · 物理学 2015-06-22 Sabrina Camargo , Maik Riedl , Celia Anteneodo , Juergen Kurths , Thomas Penzel , Niels Wessel

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…

Sleep apnea, a prevalent sleep disorder, involves repeated episodes of breathing interruptions during sleep, leading to various health complications, including cognitive impairments, high blood pressure, heart disease, stroke, and even…

信号处理 · 电气工程与系统科学 2025-09-03 Chun Hin Siu , Hossein Miri

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…

声音 · 计算机科学 2023-01-31 Shenghao Li , Jagmohan Chauhan

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…

信号处理 · 电气工程与系统科学 2020-07-28 Nannapas Banluesombatkul , Thanawin Rakthanmanon , Theerawit Wilaiprasitporn

Sleep apnea is a breathing disorder where a person repeatedly stops breathing in sleep. Early detection is crucial for infants because it might bring long term adversities. The existing accurate detection mechanism (pulse oximetry) is a…

信号处理 · 电气工程与系统科学 2021-05-11 Gihan Jayatilaka , Harshana Weligampola , Suren Sritharan , Pankayraj Pathmanathan , Roshan Ragel , Isuru Nawinne

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…

机器学习 · 计算机科学 2021-12-20 Hosna Ghandeharioun

The ability to assess sleep at home, capture sleep stages, and detect the occurrence of apnea (without on-body sensors) simply by analyzing the radio waves bouncing off people's bodies while they sleep is quite powerful. Such a capability…

Polysomnography (PSG) is a type of sleep study that records multimodal physiological signals and is widely used for purposes such as sleep staging and respiratory event detection. Conventional machine learning methods assume that each sleep…

信号处理 · 电气工程与系统科学 2024-02-29 Hamed Fayyaz , Abigail Strang , Niharika S. D'Souza , Rahmatollah Beheshti

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…

声音 · 计算机科学 2026-02-03 Xiaolei Xu , Chaoyue Niu , Guy J. Brown , Hector Romero , Ning Ma

Sleep apnea syndrome requires early diagnosis because this syndrome can lead to a variety of health problems. If sleep apnea events can be detected in a noncontact manner using radar, we can then avoid the discomfort caused by the…

信号处理 · 电气工程与系统科学 2023-11-03 Takato Koda , Shigeaki Okumura , Hirofumi Taki , Satoshi Hamada , Hironobu Sunadome , Susumu Sato , Kazuo Chin , Takuya Sakamoto

Identifying sleep problem severity from overnight polysomnography (PSG) recordings plays an important role in diagnosing and treating sleep disorders such as the Obstructive Sleep Apnea (OSA). This analysis traditionally is done by…

机器学习 · 计算机科学 2020-06-16 Longlong Feng , Xu Wang

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,…

Snoring is extremely common in the general population and when irregular may indicate the presence of obstructive sleep apnea. We analyze the overnight sequence of wave packets --- the snore sound --- recorded during full polysomnography in…

Polysomnography (PSG), the current gold standard method for monitoring and detecting sleep disorders, is cumbersome and costly. At-home testing solutions, known as home sleep apnea testing (HSAT), exist. However, they are contact-based, a…

计算机视觉与模式识别 · 计算机科学 2024-08-08 Kai Del Regno , Alexander Vilesov , Adnan Armouti , Anirudh Bindiganavale Harish , Selim Emir Can , Ashley Kita , Achuta Kadambi

The abnormal pause or rate reduction in breathing is known as the sleep-apnea hypopnea syndrome and affects the quality of sleep of an individual. A novel method for the detection of sleep apnea events (pause in breathing) from peripheral…

机器学习 · 计算机科学 2021-12-22 Arlene John , Koushik Kumar Nundy , Barry Cardiff , Deepu John

Apnea is a common sleep disorder characterized by breathing interruptions lasting at least ten seconds and occurring more than five times per hour. Accurate, high-temporal-resolution detection of sleep apnea subtypes - Obstructive, Central,…

信号处理 · 电气工程与系统科学 2025-08-06 Zahra Mohammadi , Siamak Mohammadi

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…

信号处理 · 电气工程与系统科学 2019-06-25 Valentin Thorey , Albert Bou Hernandez , Pierrick J. Arnal , Emmanuel H. During

Radar-based respiratory measurement is a promising tool for the noncontact detection of sleep apnea. Our team has reported that apnea events can be accurately detected using the statistical characteristics of the amplitude of respiratory…

信号处理 · 电气工程与系统科学 2025-05-27 Kodai Hasegawa , Shigeaki Okumura , Hirofumi Taki , Hironobu Sunadome , Satoshi Hamada , Susumu Sato , Kazuo Chin , Takuya Sakamoto
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