Simulation and Measurement of Human Respiration and Heartbeat with Millimeter- Wave Radar

This paper establishes a multi-scattering point chest wall motion model by combining the human respiration signal (RS) and HS (HS) measured by radar. An algorithmic process is designed based on the model to accurately separate the human respiration and heartbeat motion. Firstly, a human maximum motion velocity constraint method is proposed to correct human chest wall tracking, determine the radial position of the chest wall relative to the radar, and extract the phase signal corresponding to the chest wall motion. Then an improved time-difference method is proposed to suppress the interference of RS harmonics on HS and the interference of low-frequency noise on RS. Finally, an adaptive Gaussian weighting filter is designed to extract the RS with less distortion from the phase signal. A low-order finite-length unit impulse response (FIR) filter is used to extract the HS with less distortion from the phase signal. To verify the effectiveness of the proposed algorithm, simulating the process of measuring the RS and HS of the chest wall motion model by radar. The simulation results show that, ideally, the radar measurement results of the RS and HS are less distorted relative to the actual values. In addition, we used a millimeter-wave experimental radar system in the 60 GHz band to measure the respiration rate (RR) and HR (HR) of two subjects. The experimental results showed that the measured RR and HR correlated well with the actual values. The quantitative analysis of simulation results and experimental results show that the proposed method can achieve accurate and robust measurement of RS and HS.