Paper Title
Smart Detection Algorithm For Snoring And Apnea

To evaluate sleep quality, it is necessary to be able to accurately measure and analyze sleep disorders such as snoring or apnea. In recent years, sleep care applications and devices have been introduced, but accurate measurement techniques are required because these applications and devices do not take users’ snoring intensity and characteristics into consideration. In this paper, we proposed a smart snoring measurement method and algorithm that correct the data measured in sensors by considering regular snoring characteristic and snoring sound strength that vary from person to person. Furthermore, the proposed algorithm was developed to detect more than 10 seconds of apnea so that the degree of sleep disorders can be evaluated. In addition, we have proved the cognitive performance of the proposed algorithm through experiments and suggested ways to improve the accuracy in the PSQI index, which indicates quality of sleep in the sleep medicine field. Keywords- Internet of Things, Snoring, Apnea, Smart Algorithm, Sensor, PSQI