Paper Title: Obstructive Sleep Apnea Detection Based on Sound Interval Frequency using Wearable Device

Abstract:

This paper introduces an automated approach to identify the existence of Resistant Obstructive Sleep Apnea depending on breathing signal. The behavior of the breathing sounds is carried by decision making sound interval that detect respiratory signal when breathe and hold breathing. We have used the capability of recording breathing sound by a microphone and analyzed by sound frequency presence. Whether the recording data is abnormal has been analyzed with Audacity software. Respiratory signals are successfully analyzed by the decision making sound interval frequency made with 89.4% accuracy.