Radar-based techniques for detecting vital signs have shown promise for continuous contactless vital sign sensing and healthcare applications. However, real-world indoor environments face significant challenges for existing vital sign monitoring systems. These include signal blockage in non-line-of-sight (NLOS) situations, movement of human subjects, and alterations in location and orientation. Additionally, these existing systems failed to address the challenge of tracking multiple targets simultaneously. To overcome these challenges, we present MEDUSA, a novel coherent ultra-wideband (UWB) based distributed multiple-input multiple-output (MIMO) radar system, especially it allows users to customize and disperse the $16 \times 16$ into sub-arrays. MEDUSA takes advantage of the diversity benefits of distributed yet wirelessly synchronized MIMO arrays to enable robust vital sign monitoring in real-world and daily living environments where human targets are moving and surrounded by obstacles. We've developed a scalable, self-supervised contrastive learning model which integrates seamlessly with our hardware platform. Each attention weight within the model corresponds to a specific antenna pair of Tx and Rx. The model proficiently recovers accurate vital sign waveforms by decomposing and correlating the mixed received signals, including comprising human motion, mobility, noise, and vital signs. Through extensive evaluations involving 21 participants and over 200 hours of collected data (3.75 TB in total, with 1.89 TB for static subjects and 1.86 TB for moving subjects), MEDUSA's performance has been validated, showing an average gain of 20% compared to existing systems employing COTS radar sensors. This demonstrates MEDUSA's spatial diversity gain for real-world vital sign monitoring, encompassing target and environmental dynamics in familiar and unfamiliar indoor environments.

翻译：基于雷达的生命体征检测技术在连续非接触式生命体征感知及医疗健康应用中展现出前景。然而，在真实室内环境中，现有生命体征监测系统面临着显著挑战，包括非视距（NLOS）场景下的信号遮挡、人体目标的移动以及位置和朝向的变化。此外，现有系统未能解决同时追踪多个目标的难题。为克服这些挑战，我们提出MEDUSA——一种新型相干超宽带（UWB）分布式多输入多输出（MIMO）雷达系统，其独特之处在于允许用户将$16 \times 16$阵列定制分散为子阵列。MEDUSA利用分布式但无线同步的MIMO阵列的多样性优势，在人类目标移动且被障碍物包围的真实世界及日常生活环境中实现稳健的生命体征监测。我们开发了一种可扩展的自监督对比学习模型，该模型无缝集成至硬件平台，其中每个注意力权重对应特定的发射-接收天线对。该模型通过分解并关联包含人体运动、移动性、噪声及生命体征的混合接收信号，高效恢复准确的生命体征波形。基于21名参与者、超200小时采集数据（总计3.75 TB，其中静态目标1.89 TB、移动目标1.86 TB）的广泛评估验证了MEDUSA的性能，相较于采用商用现货（COTS）雷达传感器的现有系统，其平均增益达20%。这证明了MEDUSA在真实世界生命体征监测中的空间分集增益，可适应熟悉与陌生室内环境中的目标及环境动态变化。