A NEW APPROACH TO DIAGNOSE SLEEP APNEA SYNDROME USING A CONTINUOUS WAVELET TRANSFORM

被引：0

作者：

Zhang, Zhong ^{[1
]}

Sawamura, Ikki ^{[1
]}

Toda, Hiroshi ^{[1
]}

Akiduki, Takuma ^{[1
]}

Miyake, Tetsuo ^{[1
]}

机构：

[1] Toyohashi Univ Technol, Dept Mech Engn, 1-1 Hibarigaoka Tenpaku Cho, Toyohashi, Aichi 4418580, Japan

来源：

PROCEEDINGS OF 2015 INTERNATIONAL CONFERENCE ON WAVELET ANALYSIS AND PATTERN RECOGNITION (ICWAPR) | 2015年

关键词：

Sleep Apnea Syndrome; Continuous Wavelet Transform; Gabor Wavelet; Snoring; Breathing rhythm;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Currently, it is said that potential sufferers of Sleep Apnea Syndrome (SAS) account for up up to about 2% of the population in Japan. Not only does SAS cause lack of concentration during the day, it may also cause complications such as hypertension and heart failure, and it has been called a modern disease. However, there is a problem that it is impossible to decide if one suffers from it. And diagnosis is difficult if a patient does not go to hospital, because diagnosis requires many resources. Therefore, we propose a method that can easily diagnose SAS by the continuous wavelet transform (CWT) using a vocal sound signal, and obtain encouraging results.

引用

页码：128 / 132

页数：5