Wi-Mapping: A WiFi-based Respiration Detection System Using Complex Plane Mapping
Chen Zhang, Ting Jiang, Xinyi Zhou, Danlan Huang · 2024
Respiration serves as a critical indicator of human health, reflecting the well-being of various bodily organs. The potential of device-free WiFi signals for respiration detection has been shown in recent investigations. Nevertheless, there are several disadvantages to the current WiFi signal-based respiration detection methods. These include inadequate utilization of the respiratory component within the signal, and the high-quality subcarriers cannot be screened out effectively. In response to these issues, we propose a novel respiration detection system named Wi-Mapping. Firstly, to enhance the utilization of the respiratory component within the signal, we introduce a novel complex plane mapping approach. This method reconstructs a signal with a more noticeable respiratory component by integrating the original amplitude and phase of Channel State Information (CSI). Wi-Mapping then concentrates on utilizing features in the frequency domain and subcarrier dimension. Additionally, a subcarrier screening method is proposed, which combines Respiration Energy Ratio (RER) and correlation between subcarriers. This method can effectively screen out subcarriers with higher quality. Finally, a dataset containing various scenes was established to confirm Wi-Mapping’s respiration detecting capabilities. The detection error achieved by Wi-Mapping is 0.382, with a detection rate of 86.91%, surpassing that of state-of-the-art methods.