Signal shape feature for automatic snore and breathing sounds classification

Emoto, Takahiro, Kashihara, Masato, Abeyratne, Udantha R, Kawata, Ikuji, Akutagawa, Masatake, Konaka, Shinsuke and kinouchi, Yohsuke (2014) Signal shape feature for automatic snore and breathing sounds classification. Physiological Measurement, 35 12: 2489-2499. doi:10.1088/0967-3334/35/12/2489

Author Emoto, Takahiro
Kashihara, Masato
Abeyratne, Udantha R
Kawata, Ikuji
Akutagawa, Masatake
Konaka, Shinsuke
kinouchi, Yohsuke
Title Signal shape feature for automatic snore and breathing sounds classification
Journal name Physiological Measurement   Check publisher's open access policy
ISSN 1361-6579
Publication date 2014-12
Year available 2014
Sub-type Article (original research)
DOI 10.1088/0967-3334/35/12/2489
Open Access Status
Volume 35
Issue 12
Start page 2489
End page 2499
Total pages 11
Place of publication Bristol, United Kingdom
Publisher Institute of Physics Publishing
Collection year 2015
Language eng
Formatted abstract
Snore analysis techniques have recently been developed for sleep studies. Most snore analysis techniques require reliable methods for the automatic classification of snore and breathing sounds in the sound recording. In this study we focus on this problem and propose an automated method to classify snore and breathing sounds based on the novel feature, 'positive/negative amplitude ratio (PNAR)', to measure the shape of the sound signal. The performance of the proposed method was evaluated using snore and breathing recordings (snore: 22643 episodes and breathing: 4664 episodes) from 40 subjects. Receiver operating characteristic (ROC) analysis showed that the proposed method achieved 0.923 sensitivity with 0.918 specificity for snore and breathing sound classification on test data. PNAR has substantial potential as a feature in the front end of a non-contact snore/breathing-based technology for sleep studies.
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2015 Collection
School of Information Technology and Electrical Engineering Publications
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Citation counts: TR Web of Science Citation Count  Cited 1 times in Thomson Reuters Web of Science Article | Citations
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Created: Fri, 12 Dec 2014, 19:23:08 EST by Dr Udantha Abeyratne on behalf of School of Information Technol and Elec Engineering