Noncontact Multipoint Vital Sign Monitoring With mmWave MIMO Radar
Wei Ren, Jiannong Cao, Huansheng Yi, Kaiyue Hou, Minqi Hu, Jianqi Wang, Fugui Qi
Abstract
Multipoint vital sign monitoring is essential for providing detailed insights into physiological changes. Traditional single-sensor approaches are inadequate for capturing multipoint vibrations. Existing contact-based solutions, while addressing this need, can cause discomfort and skin allergies, whereas noncontact optical and acoustic methods are highly susceptible to light interference and environmental noise. In this article, we aim to develop a noncontact, multipoint vital sign monitoring technique using multiple-input-multiple-output (MIMO) radar, focused on physically differentiating and precisely measuring chest-wall surface vibrations at multiple points induced by cardiopulmonary mechanical activity. The primary challenges in developing such a technique involve developing algorithms to extract and separate entangled signals, as well as establishing a reliable method for validating detection accuracy. To address these limitations, we introduce MultiVital, a wireless system that leverages mmWave MIMO radar for synchronous multipoint vital sign monitoring. It integrates two reference modalities: five-channel seismocardiography (SCG) sensors and a one-channel electrocardiogram (ECG) electrode, enabling comprehensive radar-based research and performance validation across multiple physiological metrics. In addition, we have developed a multimodal signal processing framework, consisting of a radar signal processing module, an SCG calibration module, and a spatial alignment scheme. To evaluate the radar signal processing module, we conducted mathematical derivation and simulation. The experimental results indicate that the noncontact MultiVital system achieves multipoint synchronous monitoring with high precision, highly consistent with the results from reference modalities. This system enables precise detection of subtle cardiopulmonary movements in different regions of the human body, providing more accurate and comprehensive information for cardiopulmonary health monitoring.