对比三种雷达在卧室人体活动监测中的表现，发现各有优劣。
A comparison between ceiling-mounted FMCW, IR-UWB and Wi-Fi radar for in-bedroom human activity monitoring and sleep interruption detection
- 同环境部署下比较FMCW、IR-UWB和Wi-Fi雷达性能
- IR-UWB识别准确率最高（89.0%宏F1），FMCW适应新布局能力最强（83.8%宏F1）
- 适用于智能健康监测系统选型参考
尽管基于射频的无接触医疗监测技术日益重要，但频率调制连续波（FMCW）雷达、脉冲无线电超宽带（IR-UWB）和Wi-Fi感知等不同无线技术很少在相同部署条件下进行比较，现有研究通常在硬件、数据集和评估方法上存在差异。此外，尽管天花板安装雷达在医疗环境中具有实际部署和成本优势，其性能仍鲜有深入研究。因此，本文通过20名参与者在六种房间布局下的同步数据，对天花板安装的FMCW、IR-UWB和Wi-Fi感知进行了受控对比分析。所有技术均使用相同的卷积神经网络（CNN）在细粒度10类人体活动识别（HAR）任务和粗粒度4类睡眠监测任务上进行评估。IR-UWB在跨被试活动识别中表现最佳（89.0%宏F1），FMCW在未见房间布局下泛化能力最强（83.8%宏F1）。对于睡眠监测，所有技术在未见环境中均超过92%宏F1。结果揭示了识别性能与环境鲁棒性之间的根本权衡，可归因于测距分辨率、天线多样性、多普勒分辨率及空间信息保留等方面的差异。这些发现为面向医疗的射频感知系统设计提供了实用指导。
原文摘要 · Abstract (English)
Despite their growing importance for contact-free radio frequency (RF) based healthcare monitoring, different radio technologies such as frequency-modulated continuous wave (FMCW) radar, impulse radio ultra-wideband (IR-UWB), and Wi-Fi sensing are rarely compared under identical deployment conditions, as existing studies typically differ in hardware, datasets, and evaluation methodologies. In addition, the performance of ceiling-mounted radars, despite their practical deployment and cost advantages in healthcare environments, remain underexplored. Therefore, this paper presents a controlled comparison and analysis of ceiling-mounted FMCW, IR-UWB, and Wi-Fi sensing using synchronized recordings from 20 participants across six room layouts. All technologies are evaluated with the same convolutional neural network (CNN) on both a fine-grained 10-class human activity recognition (HAR) task and a coarse 4-class sleep monitoring task. IR-UWB achieves the highest cross-subject activity recognition performance (89.0% macro F1), while FMCW generalizes best to unseen room layouts (83.8% macro F1). For sleep monitoring, all technologies exceed 92% macro F1 in unseen environments. The results reveal a fundamental trade-off between recognition performance and environmental robustness, which can be explained through differences in range resolution, antenna diversity, Doppler resolution, and spatial information retention. These findings provide practical guidelines for the design of healthcare-oriented RF sensing systems.
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