A new approach to diagnose Sleep Apnea Syndrome using a continuous wavelet transform
Zhong Zhang, Ikki Sawamura, Hiroshi Toda, Takuma Akiduki, Tetsuo Miyake · 2015
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.