mmWave Radar-Based Multi-Target Vital Signs Monitoring for Unsteady Scenarios

Frequency Modulated Continuous Wave (FMCW)-based mmWave radar has attracted widespread attention due to its non-contact and high spatial resolution for multi-target vital signs monitoring. However, current works mostly focus on how to improve detection performance under the steady scenarios with a single target, while unsteady scenarios and physical mutual interference from multiple targets are rarely considered. In this work, we propose an innovative method for multi-target vital signs for unsteady scenarios, such as aerobic exercise. The method automatically distinguishes between steady state and motion state, and completes a best-effort vital signs detection during unsteady state. To differentiate multiple targets, we design a weight vector enhancement method combined with target space localization, and then, apply the variational mode decomposition (VMD) algorithm to extract the respiratory and heart rates of a single target. Moreover, for evaluating the efforts of exercise, we propose Multi-target Motion Recognition (MMR) based on MobileNet-V2 network to recognize the motion states of multiple targets. The experimental results showed that the mean absolute error of respiratory rate and heart rate decreased to 1.37 bpm and 2.56 bpm, respectively. Meanwhile, the MMR algorithm achieves close to 98.1% accuracy in recognizing motion states.