Authors:
Tsuyoshi Mikami
1
;
Satoshi Ueki
2
;
Hirotaka Takahashi
2
and
Kazuya Yonezawa
3
Affiliations:
1
National Institute of Technology, Japan
;
2
Nagaoka University of Technology, Japan
;
3
National Hospital Organization Hakodate Hospital, Japan
Keyword(s):
Snoring Sounds, Hilbert-Huang Transform, Sleep Apnea Syndrome.
Related
Ontology
Subjects/Areas/Topics:
Acoustic Signal Processing
;
Applications and Services
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Medical Image Detection, Acquisition, Analysis and Processing
;
Physiological Processes and Bio-Signal Modeling, Non-Linear Dynamics
Abstract:
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.