DocumentCode :
504437
Title :
Detecting nonlinearity in prediction residuals of snoring sounds
Author :
Mikami, Tsuyoshi
Author_Institution :
Tomakomai Coll. of Technol., Tomakomai, Japan
fYear :
2009
fDate :
18-21 Aug. 2009
Firstpage :
5256
Lastpage :
5259
Abstract :
This paper focuses on the nonlinear properties of snoring sounds for the purpose of obstructive sleep apnea diagnosis. Snoring sounds are convolutional sounds caused by wheezing of airway obstruction and oscillation of soft palate. Namely, it should be natural that the snoring sounds are generated from a nonlinear dynamics, but the nonlinear properties of them have not yet been studied so far. In this paper, the nonlinearity is defined as the predictability using a linear AR prediction model, and the prediction residuals are analyzed by portmanteau test.
Keywords :
acoustic signal detection; autoregressive processes; bioacoustics; medical disorders; medical signal detection; medical signal processing; patient diagnosis; pneumodynamics; sleep; statistical testing; OSA syndrome; acoustic signal acquisition; airway obstruction wheezing; convolutional sound; linear AR prediction model; nonlinear dynamics detection; obstructive sleep apnea syndrome diagnosis; portmanteau test; snoring sound prediction residual; soft palate oscillation; Acoustic noise; Acoustic testing; Convolution; Convolutional codes; Educational institutions; Frequency domain analysis; Predictive models; Sleep apnea; Tongue; White noise; Linear Prediction Model; Nonlinearity; Portmanteau Test; Snoring Sounds;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
ICCAS-SICE, 2009
Conference_Location :
Fukuoka
Print_ISBN :
978-4-907764-34-0
Electronic_ISBN :
978-4-907764-33-3
Type :
conf
Filename :
5333345
Link To Document :
بازگشت