Nasal pressure recordings for automatic snoring detection.

Abstract

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.

• Authors: Hyo-Ki Lee, Hojoong Kim, Kyoung-Joung Lee
• Journal: Medical & biological engineering & computing (Med Biol Eng Comput) Vol. 53 Issue 11 Pg. 1103-11 (Nov 2015) ISSN: 1741-0444 [Electronic] United States
• PMID: 26392181 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)

Topics

• Aged
• Algorithms
• Female
• Humans
• Male
• Middle Aged
• Nose (physiology)
• Polysomnography (methods)
• Pressure
• Sensitivity and Specificity
• Signal Processing, Computer-Assisted
• Snoring (diagnosis, physiopathology)