An Efficient Noncontact Method for Monitoring of Respiratory Rate During Sleep Using Wireless Signals

Abstract

Monitoring of respiratory rate during sleep is very important to prevent a vital condition caused by sleep disorders, especially in non-clinical settings. Conventional methods require many probes connected to various parts of the human body, as well as clinical environments for the measurements. Therefore, noncontact systems have recently attracted attention. In this paper, an efficient noncontact method for the monitoring of respiratory rate during sleep by using wireless radio signals, is proposed. The proposed noncontact system can successfully separate body movements (turnovers), breath holding (apnea) and breathing cases. In this paper, the frequency estimation algorithm, Quinn and Fernandes (QF) method is firstly adapted and used for the respiratory rate estimation. It is shown with the experiments conducted compatible with real-world settings and measurements that the QF method is robust to poor initial estimates, is effective for different sleeping postures and distances, and outperforms the existing benchmark estimation methods.