Smart device for long-term sleep monitoring at home

This work aims to develop an autonomous and non-intrusive sleep monitoring system to provide information on the stages and quality of sleep. We propose an original data scoring algorithm. The goal is to help physicians to have relevant data on the patient's sleep at home. This solution would be a complementary solution to the polysomnography (PSG) standard method, which is more intrusive, expensive and difficult for long-term home monitoring. The proposed solution is based on worn devices for measuring data movements associated with a classification algorithm of the sleep stages: awakening, light sleep, deep sleep and rapid eye movement (REM).