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使用FMCW雷达估计心率:为车载应用评估的两阶段方法

Jonas Brandstetter^1,2, Eva-Maria Knoch¹, Frank Gauterin¹

¹Faculty of Mechanical Engineering, Institute for Vehicle Systems Engineering, Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany.

Biomimetics (Basel, Switzerland)

|September 26, 2025

概括

这项研究引入了一种基于雷达的新型系统,用于无接触驾驶员在车辆中监测心率 (HR). 该方法实现了准确的HR估计,这对于提高驾驶员安全系统至关重要.

科学领域:

汽车安全汽车安全
生物医学工程生物医学工程
传感器技术传感器技术

背景情况:

驾驶员监控对于车辆安全至关重要,人类因素导致大多数事故.
由于运动和环境因素,车辆中的无接触心率 (HR) 测量具有挑战性.

研究的目的:

开发和验证一种新的两阶段方法,用于使用60 GHz FMCW雷达进行准确的无接触驾驶员HR估计.
改进驾驶员实时状态评估,用于先进的车辆安全系统.

主要方法:

一种两阶段的HR估计方法,结合了离散波形变换 (DWT),自回归 (AR) 光谱分析和相关性向量机 (RVM).
序列卡尔曼选 (SKF) 用于稳定HR估计.
在车辆的防晒罩中使用Infineon BGT60TR13C雷达模块实现.

主要成果:

实现了强大而准确的HR估计,与商业可穿戴设备相提并论.
在现实驾驶条件下成功与极地H10胸进行验证.
在短的测量窗口 (5s) 和各种照明/服装条件下,已证明有效.

结论:

拟议的基于雷达的系统为动态汽车环境中的无接触驾驶员人力资源监控提供了可行的解决方案.
这种方法通过将生物生命体知觉原理应用于汽车传感学来推进仿生学.
未来的工作包括与视觉方法的传感器融合以及对增强的驾驶员监控系统 (DMS) 的心率变化 (HRV) 估计.

关键词:

在FMCW雷达.卡尔曼过器可以过.离散的波形变换.驾驶员监控系统驾驶员监控系统估计心率的心率估计车载应用车载应用在现实世界中验证.相关性矢量机器相关性矢量机器监测生命体征,监测生命体征.

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