Nasal pressure recordings for automatic snoring detection

This study presents a rule-based method for automated, real-time snoring detection using nasal pressure recordings during overnight sleep. Although nasal pressure recordings provide information regarding nocturnal breathing abnormalities in a polysomnography (PSG) study or continuous positive airway...

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Published in:Medical & biological engineering & computing 2015-11, Vol.53 (11), p.1103-1111
Main Authors: Lee, Hyo-Ki, Kim, Hojoong, Lee, Kyoung-Joung
Format: Article
Language:English
Subjects:
Acoustics
Aged
Algorithms
Analysis
Assessments
Automation
Biomedical and Life Sciences
Biomedical Engineering and Bioengineering
Biomedicine
Body mass index
Computer Applications
Cost analysis
Female
Human Physiology
Humans
Imaging
Male
Medical diagnosis
Microphones
Middle Aged
Nose
Nose - physiology
Original Article
Patients
Polysomnography - methods
Pressure
Radiology
Real time
Recording
Respiration
Sensitivity and Specificity
Sensors
Signal Processing, Computer-Assisted
Sleep
Sleep apnea
Sleep deprivation
Sleep disorders
Snoring - diagnosis
Snoring - physiopathology
Software
Studies
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cited_by cdi_FETCH-LOGICAL-c578t-466ec7bd5b1f679dc0d5b120b13e9e7198b2b133f38431bce3fe00e14cb0a4053
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creator Lee, Hyo-Ki
Kim, Hojoong
Lee, Kyoung-Joung
description This study presents a rule-based method for automated, real-time snoring detection using nasal pressure recordings during overnight sleep. Although nasal pressure recordings provide information regarding nocturnal breathing abnormalities in a polysomnography (PSG) study or continuous positive airway pressure (CPAP) system, an objective assessment of snoring detection using these nasal pressure recordings has not yet been reported in the literature. Nasal pressure recordings were obtained from 55 patients with obstructive sleep apnea. The PSG data were also recorded simultaneously to evaluate the proposed method. This rule-based method for automatic, real-time snoring detection employed preprocessing, short-time energy and the central difference method. Using this methodology, a sensitivity of 85.4 % and a positive predictive value of 92.0 % were achieved in all patients. Therefore, we concluded that the proposed method is a simple, portable and cost-effective tool for real-time snoring detection in PSG and CPAP systems that does not require acoustic analysis using a microphone.
doi_str_mv 10.1007/s11517-015-1388-2
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ispartof Medical & biological engineering & computing, 2015-11, Vol.53 (11), p.1103-1111
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1741-0444
language eng
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subjects Acoustics
Aged
Algorithms
Analysis
Assessments
Automation
Biomedical and Life Sciences
Biomedical Engineering and Bioengineering
Biomedicine
Body mass index
Computer Applications
Cost analysis
Female
Human Physiology
Humans
Imaging
Male
Medical diagnosis
Microphones
Middle Aged
Nose
Nose - physiology
Original Article
Patients
Polysomnography - methods
Pressure
Radiology
Real time
Recording
Respiration
Sensitivity and Specificity
Sensors
Signal Processing, Computer-Assisted
Sleep
Sleep apnea
Sleep deprivation
Sleep disorders
Snoring - diagnosis
Snoring - physiopathology
Software
Studies
title Nasal pressure recordings for automatic snoring detection
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