A Real-time Respiration Monitoring System Using WiFi-Based Radar Model

This paper proposes and experimentally validates a novel WiFi-based radar model for indoor WiFi sensing, which enables accurate measurement of the radial velocity of objects. A human respiratory monitoring system based on the proposed WiFi radar model is developed. The respiratory monitoring system also leverages principal component analysis (PCA) on the MIMO WiFi channel state information ratio (CSIR) information to extract the components related to human activities. Doppler frequency of respiratory motion is obtained from time-frequency analysis of the CSIR through short-time Fourier transform (STFT). Experimental results show that the WiFi-based radar model achieves high accuracy in velocity measurement with an average error of less than 1.5% and can be used to real-time monitor the respiration rate.