Detecting Nonlinear Properties of Snoring Sounds for Sleep Apnea Diagnosis
This paper investigates nonlinear properties of snoring sounds by a surrogate analysis which is generally used to verify the existence of nonlinearity in a time series. The ultimate goal of this study is to extract useful information from the nonlinear properties of snores so as to diagnose obstructive sleep apnea. For such purpose, many researchers have examined snoring sounds by linear frequency analysis such as Fourier Transform or Linear Predictive Coding, but the nonlinear properties of snores have not yet been clarified and the existence of nonlinearity has not been proved so far. The author adopts correlation integral to evaluate the geometrical nonlinear structure of snore attractors quantitatively. As a result of experiments, nonlinear properties are found in some kinds of waveform. But a complex waveform, in which no prominent peaks are found in the amplitude spectrum, does not have a nonlinear property.
snoring sounds nonlinear dynamics chaos analysis medical diagnosis
Tsuyoshi Mikami
Dept. Computer Science & Engineering Tomakomai College of Technology Tomakomai, Japan
国际会议
上海
英文
1173-1176
2008-05-16（万方平台首次上网日期，不代表论文的发表时间）