Device-Free Multi-Person Respiration Monitoring Using WiFi

Abstract

Device-free respiration wireless monitoring is an emerging vital sign monitoring technique which could estimate respiration rate in a contactless manner by analyzing the cyclical influence of human respiration on surrounding wireless signals. This technique has a wide application prospect in the fields of intelligent vehicles, fatigue driving detection, and smart space. State-of-art methods have achieved excellent performance in monitoring the respiration of a single person. However, when there are multi-person need to be monitored simultaneously, most of existing methods will fail due to the aliasing of multiple respiratory signals. To solve this problem, we explore to separate multiple respiratory signals through a multi-domain analysis method. Specifically, we try to observe the influenced wireless signals from both the Doppler domain and angle of arrival (AoA) domain. We design a super resolution method to build the two-dimensional Doppler AoA map (DAM), and then, estimate the respiration rate of each person by clustering and analyzing the DAM. Experimental results on commodity WiFi hardware show that it can monitor the respiration rate of three persons simultaneously with an accuracy of 97.5%.