Detecting nonlinearity in prediction residuals of snoring sounds

Detecting nonlinearity in prediction residuals of snoring sounds

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 f...

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Bibliographische Detailangaben
1. Verfasser: Mikami, T.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Acoustic noise
Acoustic testing
Convolution
Convolutional codes
Educational institutions
Frequency domain analysis
Linear Prediction Model
Nonlinearity
Portmanteau Test
Predictive models
Sleep apnea
Snoring Sounds
Tongue
White noise
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Beschreibung
Zusammenfassung: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.