Analysing snoring sounds for obstructive sleep apnea (OSA) patients Obstrükti̇f uyku apnesi̇ (osa) hastalari i̇çi̇n horlama sesleri̇ni̇n anali̇zi̇

Çavuşoǧlu, Mustafa
Serinağaoğlu Doğrusöz, Yeşim
Eroǧul, Osman
Several studies have done in order to determine the relationship between snoring and obstructive sleep apnea syndrome (OSAS). One of the common problem that is faced during the medical treatment of the apnea is the undetermination of the efficiency of the applied treatment in terms of objective criteria. It is needed to automatically detect each snoring episode in order to estimate the spectral features and determine the snoring sound intensity. In this study, an automatic detection system of acoustic snoring signals has been designed, to work with long duration respiratory sound recordings. The system was designed to select snoring episodes from simple snorers and OSAS patients and to reject the undesired waveforms. The sound recordings were taken from patients that are suspected of OSAS pathology while they were connected to the polysomnography in Gulhane Military Medical Academy (GMMA) Sleep Studies Laboratory. In order to validate the system, 500 snores were analysed taken from 30 patients with different apnea/hypopnea index (AHI). Results were compared with manual annotations done by a medical doctor and the average sensitivity of the system is determined as 86%.


Detection of post apnea sounds and apnea periods from sleep sounds
Karcı, Ersin; Serinağaoğlu Doğrusöz, Yeşim; Çiloğlu, Tolga; Department of Electrical and Electronics Engineering (2011)
Obstructive Sleep Apnea Syndrome (OSAS) is defined as a sleep related breathing disorder that causes the body to stop breathing for about 10 seconds and mostly ends with a loud sound due to the opening of the airway. OSAS is traditionally diagnosed using polysomnography, which requires a whole night stay at the sleep laboratory of a hospital, with multiple electrodes attached to the patient's body. Snoring is a symptom which may indicate presence of OSAS; thus investigation of snoring sounds, which can be r...
Leveraging Multimodal and Feature Selection Approaches to Improve Sleep Apnea Classification Performance
Memiş, Gökhan; Sert, Mustafa; Yazıcı, Adnan (2017-05-15)
Obstructive sleep apnea (OSA) is a sleep disorder with long-term adverse effects such as cardiovascular diseases. However, clinical methods, such as polisomnograms, have high monitoring costs due to long waiting times and hence efficient computer-based methods are needed for diagnosing OSA. In this study, we propose a method based on feature selection of fused oxygen saturation and electrocardiogram signals for OSA classification. Specifically, we use Relieff feature selection algorithm to obtain robust fea...
Spectral envelope analysis for simple snorers and obstructive sleep apnea patients Tikanmaya baǧli uyku apnesi̇ hastalari ve basi̇t horlayanlarda horlama sesleri̇ni̇n i̇zgesel zarf i̇ncelemesi̇
Çavuşoǧlu, Mustafa; Kamaşak, Mustafa; Eroǧul, Osman; Çiloğlu, Tolga; Serinağaoğlu Doğrusöz, Yeşim; Birkent, Hakan (2007-01-01)
In recent years, several studies have shown the relationship between snoring and obstructive sleep apnea syndrome (OSAS). Instead of time domain analysis of snoring signal, the spectral features and shapes of snores have been found different in simple snorers and OSAS patients. In this study, we propose a method to differentiate simple snorers and OSAS patients based on spectral envelope estimation of snoring signals. Formant frequencies and bandwidths are computed for both groups and the variation and cons...
An efficient fast method of snore detection for sleep disorder investigation
Çavuşoğlu, Mustafa; Serinağaoğlu Doğrusöz, Yeşim; Department of Electrical and Electronics Engineering (2007)
Snores are breath sounds that most people produce during sleep and they are reported to be a risk factor for various sleep disorders, such as obstructive sleep apnea syndrome (OSAS). Diagnosis of sleep disorders relies on the expertise of the clinician that inspects whole night polysomnography recordings. This inspection is time consuming and uncomfortable for the patient. There are surgical and therapeutic treatments. However, evaluation of the success of these methods also relies on subjective criteria an...
Automated detection of sleep spindles
Görür, Dilan; Gençer, Nevzat G.; Halıcı, Uğur; Department of Electrical and Electronics Engineering (2003)
Sleep spindles are one of the rhythmic activities observed in sleep electroencephalogram (EEG). As they are well defined and functional, sleep spindle analysis is significant for brain research. Identifying the characteristics of sleep spindles may lead to an understanding of the functions of sleep. Furthermore, understanding the sleep spindle generation mechanisms can explain the other rhythmical activity occurring in other brain regions. The detection process of the sleep spindle data of a whole night sle...
Citation Formats
M. Çavuşoǧlu, Y. Serinağaoğlu Doğrusöz, and O. Eroǧul, “Analysing snoring sounds for obstructive sleep apnea (OSA) patients Obstrükti̇f uyku apnesi̇ (osa) hastalari i̇çi̇n horlama sesleri̇ni̇n anali̇zi̇,” 2006, vol. 2006, Accessed: 00, 2020. [Online]. Available: