Development of smart alarm based on sleep cycle analysis

Abstract

Sleep problem is currently a norm for many people, especially during this Covid-19 pandemic. Due to the limited number of sleep medicine studies, most people were unaware and just ignored their sleep problems. The use of polysomnography (PSG) in sleep medicine is quite popular, but due to its disturbance towards the subjects, it may decrease the subjects' sleep quality and may affect the result accuracy since it needs to be attached to the subjects' body. This work proposed a smart alarm based on the sleep cycle using speech analysis that uses a non-contact device, which is an undirected microphone of the Google AIY Voice Kit with Raspberry Pi. The microphone will be used to record the subjects' sleep sounds and detect the subjects' sleep cycle. The system will trigger a speaker attached to the Google Voice Kit to produce a sound to wake up the subject when they complete a particular sleep cycle according to their preference. Results showed that the system could detect sounds when subjects were sleeping and show a subject's sleep pattern. Whenever the subject past specific minutes, the sound amplitude is increased by 3 dB. These results indicate that subject is likely having their REM stages, and after 10 minutes, the subject will complete a sleep cycle.