Non-invasive sleep monitoring based on RFID

Abstract

Some sleep disorders, such as sleep apnea, restless legs syndromes (RLS), and periodic limb movement disorder (PLMD), require a full-night sleep monitoring for diagnosis. Conventional sleep monitoring devices are disturbing and inconvenient for daily scene applications. In this poster paper, we propose a sleep monitoring system by embedding RFID tags into bed cloth and realize two main functions: breath monitoring and body movement detection. We apply a finite impulse response low pass filter to get smooth breath signal wave and use a convolutional neural network (CNN) algorithm to identify the movement of person objects. Finally, we conduct experiments to evaluate the breath monitoring in a real world scenario. The experiment results show that our monitoring system can monitor breath with a high accuracy.