Detecting Nonlinear Acoustic Properties of Snoring Sounds using Hilbert-Huang Transform

Since snoring is known to be related to sleep apnea syndrome, many medical/physiological researchers have focused on the biomechanism of snoring and the acoustic properties. Snoring sounds are the mixture of the nonlinear oscillation sounds of the oropharyngeal soft tissues and the airflow noises during inhalation. In conventional studies, however, such properties have not been paid attention to, because there were no suitable methods for the analysis of nonlinear and nonstationary time series data. In this paper, we adopt Hilbert-Huang Transform (HHT) to clarify the nonlinear and nonstationary properties in a nasal snoring sound. As a result, two types of frequency fluctuation are found in the Hilbert-Huang spectrum.