Investigation of obstructive sleep apnea using nonlinear mode interations in nonstationary snore signals

Ng, Andrew Keong, Koh, Tong San, Abeyratne, Udantha Ranjith and Puvanendran, Kathiravelu (2009) Investigation of obstructive sleep apnea using nonlinear mode interations in nonstationary snore signals. Annals of Biomedical Engineering, 37 9: 1796-1806. doi:10.1007/s10439-009-9744-8

Author Ng, Andrew Keong
Koh, Tong San
Abeyratne, Udantha Ranjith
Puvanendran, Kathiravelu
Title Investigation of obstructive sleep apnea using nonlinear mode interations in nonstationary snore signals
Journal name Annals of Biomedical Engineering   Check publisher's open access policy
ISSN 0090-6964
Publication date 2009-06
Year available 2009
Sub-type Article (original research)
DOI 10.1007/s10439-009-9744-8
Volume 37
Issue 9
Start page 1796
End page 1806
Total pages 11
Editor Kyriacos A. Athanasiou
Place of publication New York. USA
Publisher Springer New York
Collection year 2010
Language eng
Formatted abstract
Acoustic studies on snoring sounds have recently drawn attention as a potential alternative to polysomnography in the diagnosis of obstructive sleep apnea (OSA). This paper investigates the feasibility of using nonlinear coupling between frequency modes in snore signals via wavelet bicoherence (WBC) analysis for screening of OSA. Two novel markers (PF1 and PSF), which are frequency modes with high nonlinear coupling strength in their respective WBC spectrum, are proposed to differentiate between apneic and benign snores in same- or both-gender snorers. Snoring sounds were recorded from 40 subjects (30 apneic and 10 benign) by a hanging microphone, and subsequently preprocessed within a wavelet transform domain. Forty inspiratory snores (30 as training and 10 as test data) from each subject were examined. Results demonstrate that nonlinear mode interactions in apneic snores are less self-coupled and usually occupy higher and wider frequency ranges than that of benign snores. PF1 and PSF are indicative of apneic and benign snores (p < 0.0001), with optimal thresholds of PF1 = 285 Hz and PSF = 492 Hz (for both genders combined), as well as sensitivity and specificity values between 85.0 and 90.7%, respectively, outperforming the conventional diagnostic indicator (spectral peak frequency, PF = 243–275 Hz, sensitivity = 77.7–79.7%, specificity = 72.0–78.0%, p < 0.0001). Relationships between apnea-hypopnea index and the proposed markers could likely take the functional form of exponential or power. Perspectives on nonlinear dynamics analysis of snore signals are promising for further research and development of a reliable and inexpensive diagnostic tool for OSA.
Keyword Obstructive sleep apnea
Snore signals
Acoustic analysis
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: 2010 Higher Education Research Data Collection
School of Information Technology and Electrical Engineering Publications
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 16 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 22 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Fri, 23 Apr 2010, 08:57:53 EST by Marie Walker on behalf of School of Information Technol and Elec Engineering