ResBeat: Resilient Breathing Beats Monitoring with Realtime Bimodal CSI Data

Vital signs, such as breathing rate, can provide useful information for personal healthcare. In this paper, we present ResBeat, a commodity 5GHz WiFi based system to exploit bimodal channel state information (CSI), including amplitude and phase difference, for realtime, long- term, and contact-free breathing monitoring. We first present an analysis of breathing signal anomaly based on bimodal CSI data. We then describe the data preprocessing, adaptive signal selection, and breathing signal monitoring modules of ResBeat, and employ peak detection to estimate breathing rates. We conduct extensive experiments under three different environments, where superior performance over two alternative methods is validated.