Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Spectral envelope analysis of snoring signals
Date
2008-12-01
Author
Çavuşoǧlu, Mustafa
Kamaslǎ, Mustafa
Çiloğlu, Tolga
Serinağaoğlu Doğrusöz, Yeşim
Eroǧul, Osman
Metadata
Show full item record
Item Usage Stats
153
views
0
downloads
Cite This
In recent years, several studies have shown the relationship between snoring and obstructive sleep apnea syndrome (OSAS). Besides time domain analysis of snoring signal, the spectral features and shapes of snores can be used to discriminate simple snorers and OSAS patients. In this study, we propose a method to classify simple snorers and OSAS patients based on spectral envelope estimation of snoring signals. The formant frequencies and corresponding bandwidths are computed for both group, and the variation and consistency of the formant distributions are computed. A total of 1400 snoring episodes from 7 simple snorer and 7 OSAS patients were analyzed. Significant differences are found in the formant frequencies of both groups. The results are discussed from the view point of patho-physiological aspect.
Subject Keywords
Snore
,
OSAS
,
Formant frequency
,
Spectral analysis
URI
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=63149198408&origin=inward
https://hdl.handle.net/11511/81011
https://www.researchgate.net/publication/234798736_Spectral_envelope_analysis_of_snoring_signals
Conference Name
6th IASTED International Conference on Biomedical Engineering, BioMED 2008
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
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...
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...
Mobile sleep apnea detection and monitoring based on thermocouple and pulse oximeter sensors
Demirkol Çakmak, Duygu; Eyüboğlu, Behçet Murat; Department of Electrical and Electronics Engineering (2018)
Sleep apnea syndrome is becoming a prevalent disease for both adults and children. It is described as the cessation of breath for at least 10 seconds during sleep. Detecting sleep apnea is considered as a troublesome and time-consuming method, which requires the patients to stay one or more nights in dedicated sleep disorder rooms with sensors physically attached to their body. Undiagnosed, thereby untreated, sleep apnea patients are under high risk of hypertension, heart attack, accidental injuries through...
Portable obstructive sleep apnea detection and mobile monitoring
Cakmak, Duygu Demirkol; Eyüboğlu, Behçet Murat (2017-04-10)
Obstructive sleep apnea syndrome is becoming a prevalent disease for both adults and children. It is described as the cessation of breath for at least 10 seconds during sleep. Detecting sleep apnea is considered as a troublesome and time-consuming method, which requires the patients to stay one or more nights in dedicated sleep disorder rooms with sensors physically attached to their body. Undiagnosed thereby untreated sleep apnea patients are under high risk of hypertension, heart attack, traffic accident ...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
M. Çavuşoǧlu, M. Kamaslǎ, T. Çiloğlu, Y. Serinağaoğlu Doğrusöz, and O. Eroǧul, “Spectral envelope analysis of snoring signals,” Innsbruck, Avusturya, 2008, p. 473, Accessed: 00, 2021. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=63149198408&origin=inward.