Could formant frequencies of snore signals be an alternative means for the diagnosis of obstructive sleep apnea?

Ng, Andrew Keong, Koh, Tong San, Baey, Eugene, Lee, Teck Hock, Abeyratne, Udantha Ranjith and Puvanendran, Kathiravelu (2008) Could formant frequencies of snore signals be an alternative means for the diagnosis of obstructive sleep apnea?. Sleep Medicine, 9 8: 894-898. doi:10.1016/j.sleep.2007.07.010


Author Ng, Andrew Keong
Koh, Tong San
Baey, Eugene
Lee, Teck Hock
Abeyratne, Udantha Ranjith
Puvanendran, Kathiravelu
Title Could formant frequencies of snore signals be an alternative means for the diagnosis of obstructive sleep apnea?
Journal name Sleep Medicine   Check publisher's open access policy
ISSN 1389-9457
Publication date 2008-12-01
Year available 2007
Sub-type Article (original research)
DOI 10.1016/j.sleep.2007.07.010
Open Access Status Not yet assessed
Volume 9
Issue 8
Start page 894
End page 898
Total pages 5
Editor S. Chokroverty
Place of publication Dordrecht, The Netherlands
Publisher Elsevier
Language eng
Subject 730305 Diagnostic methods
090399 Biomedical Engineering not elsewhere classified
671402 Medical instrumentation
Abstract Objective: To study the feasibility of using acoustic signatures in snore signals for the diagnosis of obstructive sleep apnea (OSA). Methods: Snoring sounds of 30 apneic snorers (24 males; 6 females; apnea-hypopnea index, AHI = 46.9 ± 25.7 events/h) and 10 benign snorers (6 males; 4 females; AHI = 4.6 ± 3.4 events/h) were captured in a sleep laboratory. The recorded snore signals were preprocessed to remove noise, and subsequently, modeled using a linear predictive coding (LPC) technique. Formant frequencies (F1, F2, and F3) were extracted from the LPC spectrum for analysis. The accuracy of this approach was assessed using receiver operating characteristic curves and notched box plots. The relationship between AHI and F1 was further explored via regression analysis. Results: Quantitative differences in formant frequencies between apneic and benign snores are found in same- or both-gender snorers. Apneic snores exhibit higher formant frequencies than benign snores, especially F1, which can be related to the pathology of OSA. This study yields a sensitivity of 88%, a specificity of 82%, and a threshold value of F1 = 470 Hz that best differentiate apneic snorers from benign snorers (both gender combined). Conclusion: Acoustic signatures in snore signals carry information for OSA diagnosis, and snore-based analysis might potentially be a non-invasive and inexpensive diagnostic approach for mass screening of OSA.
Formatted abstract
Objective
To study the feasibility of using acoustic signatures in snore signals for the diagnosis of obstructive sleep apnea (OSA).

Methods

Snoring sounds of 30 apneic snorers (24 males; 6 females; apnea–hypopnea index, AHI = 46.9 ± 25.7 events/h) and 10 benign snorers (6 males; 4 females; AHI = 4.6 ± 3.4 events/h) were captured in a sleep laboratory. The recorded snore signals were preprocessed to remove noise, and subsequently, modeled using a linear predictive coding (LPC) technique. Formant frequencies (F1, F2, and F3) were extracted from the LPC spectrum for analysis. The accuracy of this approach was assessed using receiver operating characteristic curves and notched box plots. The relationship between AHI and F1 was further explored via regression analysis.

Results
Quantitative differences in formant frequencies between apneic and benign snores are found in same- or both-gender snorers. Apneic snores exhibit higher formant frequencies than benign snores, especially F1, which can be related to the pathology of OSA. This study yields a sensitivity of 88%, a specificity of 82%, and a threshold value of F1 = 470 Hz that best differentiate apneic snorers from benign snorers (both gender combined).

Conclusion
Acoustic signatures in snore signals carry information for OSA diagnosis, and snore-based analysis might potentially be a non-invasive and inexpensive diagnostic approach for mass screening of OSA.
Keyword Obstructive Sleep Apnea
Polysomnography
snoring
acoustic analysis
formant frequencies
linear predictive coding
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ
Additional Notes Available online 6 September 2007. -- Same title available as abstract in v.8 Supp.1 Feb 2007. Young Investigator Presentations in Abstracts 2nd World Congress of the World Association of Sleep Medicine (WASM) -- http://dx.doi.org/10.1016/S1389-9457(07)70260-5

Document type: Journal Article
Sub-type: Article (original research)
Collections: Excellence in Research Australia (ERA) - Collection
School of Information Technology and Electrical Engineering Publications
 
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