Testing the system non-linearity in snoring sound via neural networks

Emoto, Takahiro, Abeyratne, Udantha R., Akutagawa, Masatake, Kinouchi, Yohsuke and Konaka, Shinsuke (2011) Testing the system non-linearity in snoring sound via neural networks. International Journal of Medical Engineering and Informatics, 3 3: 299-310. doi:10.1504/IJMEI.2011.042875

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Author Emoto, Takahiro
Abeyratne, Udantha R.
Akutagawa, Masatake
Kinouchi, Yohsuke
Konaka, Shinsuke
Title Testing the system non-linearity in snoring sound via neural networks
Journal name International Journal of Medical Engineering and Informatics   Check publisher's open access policy
ISSN 1755-0653
Publication date 2011
Sub-type Article (original research)
DOI 10.1504/IJMEI.2011.042875
Volume 3
Issue 3
Start page 299
End page 310
Total pages 12
Place of publication Olney, U.K.
Publisher Inderscience Enterprises
Collection year 2012
Language eng
Subject 0806 Information Systems
0903 Biomedical Engineering
Formatted abstract
Obstructive sleep apnea (OSA) is a serious disease caused by the collapse of upper airways during sleep. OSA is almost always accompanied by snoring. While snoring is not currently used in the clinical diagnosis of OSA, there have been intense efforts recently to model snoring for that purpose. Conventional approach is to treat snores as the outcome of a linear process and apply techniques such as linear prediction coding (LPC). However, the snores are likely to have diagnostically relevant non-linearities that cannot be captured by linear techniques. In this paper, we investigate the non-linearity of snores and develop a novel measure, as a possible characterisation index. The method is based on artificial neural networks (NN). The developed method was tested on a database of 27 subjects (5568 snoring episodes), categorised into two groups based on their respiratory disturbance index (RDI).
Keyword Obstructive sleep apnea
Snoring sounds
Artificial neural networks
Respiratory disturbance index.
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Authors prepress title: 'Testing the system nonlinearity in snoring sound via neural networks".

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Created: Mon, 27 Sep 2010, 10:53:49 EST by Jon Swabey on behalf of Faculty Of Engineering, Architecture & Info Tech