Impact of gender on snore-based obstructive sleep apnea screening

De Silva, S., Abeyratne, U. R. and Hukins, C. (2012) Impact of gender on snore-based obstructive sleep apnea screening. Physiological Measurement, 33 4: 587-601. doi:10.1088/0967-3334/33/4/587

Author De Silva, S.
Abeyratne, U. R.
Hukins, C.
Title Impact of gender on snore-based obstructive sleep apnea screening
Journal name Physiological Measurement   Check publisher's open access policy
ISSN 0967-3334
Publication date 2012-04
Sub-type Article (original research)
DOI 10.1088/0967-3334/33/4/587
Open Access Status
Volume 33
Issue 4
Start page 587
End page 601
Total pages 15
Place of publication Bristol, United Kingdom
Publisher Institute of Physics Publishing
Collection year 2013
Language eng
Abstract Obstructive sleep apnea syndrome (OSA) is a serious widespread disease in which upper airways (UA) are collapsed during sleep. OSA has marked male predominance in prevalence. Although women are less vulnerable to OSA, under-diagnosed OSA in women may associate with serious consequences. Snoring is commonly associated with OSA and one of the earliest symptoms. Snore sounds (SS) are generated due to vibration of the collapsing soft tissues of the UA. Structural and functional properties of the UA are gender dependent. SS capture these time varying gender attributed UA properties and those could be embedded in the acoustic properties of SS. In this paper, we investigate the gender-specific acoustic property differences of SS and try to exploit these differences to enhance the snore-based OSA detection performance. We developed a snore-based multi-feature vector for OSA screening and one time-measured neck circumference was augmented. Snore features were estimated from SS recorded in a sleep laboratory from 35 females and 51 males and multi-layer neural network-based pattern recognition algorithms were used for OSA/non-OSA classification. The results were K-fold cross-validated. Gender-dependent modeling resulted in an increase of around 7% in sensitivity and 6% in specificity at the decision threshold AHI = 15 against a gender-neutral model. These results established the importance of adopting gender-specific models for the snore-based OSA screening technique.
Keyword Obstructive sleep apnea
Population screening
Snore sound
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2013 Collection
School of Information Technology and Electrical Engineering Publications
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