Heart Rate Estimation Using FMCW Radar: A Two-Stage Method Evaluated for In-Vehicle Applications.

IF 3.9 3区 医学 Q1 ENGINEERING, MULTIDISCIPLINARY
Jonas Brandstetter, Eva-Maria Knoch, Frank Gauterin
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Abstract

Assessing the driver's state in real time is a critical challenge in modern vehicle safety systems, as human factors account for the vast majority of traffic accidents. Heart rate (HR) is a key physiological indicator of the driver's condition, yet contactless measurements in dynamic in-vehicle environments remain difficult due to motion artifacts, vibrations, and varying operational conditions. This paper presents a novel two-stage method for HR estimation using a commercial 60 GHz frequency-modulated continuous wave (FMCW) radar sensor, specifically designed and validated for in-vehicle applications. In the first stage, coarse HR estimation is performed using the discrete wavelet transform (DWT) and autoregressive (AR) spectral analysis. The second stage refines the estimate using an inverse application of the relevance vector machine (RVM) approach, leveraging a narrowed frequency window derived from Stage 1. Final HR estimates are stabilized through sequential Kalman filtering (SKF) across time segments. The system was implemented using an Infineon BGT60TR13C radar module installed in the sun visor of a passenger vehicle. Extensive data collection was conducted during real-world driving across diverse traffic scenarios. The results demonstrate robust HR estimations with an accuracy comparable to that of commercial wearable devices, validated against a Polar H10 chest strap. This method offers several advantages over prior work, including short measurement windows (5 s), operation under varying lighting and clothing conditions, and validation in realistic driving environments. In this sense, the method contributes to the field of biomimetics by transferring the biological principles of continuous vital sign perception to technical sensorics in the automotive domain. Future work will explore the fusion of sensors with visual methods and potential extension to heart rate variability (HRV) estimations to enhance driver monitoring systems (DMSs) further.

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基于FMCW雷达的心率估计:一种评估车载应用的两阶段方法。
在现代车辆安全系统中,实时评估驾驶员的状态是一项关键挑战,因为人为因素占绝大多数交通事故的原因。心率(HR)是驾驶员状态的关键生理指标,但由于运动伪影、振动和不同的操作条件,在动态车内环境中进行非接触式测量仍然很困难。本文提出了一种新的两阶段HR估计方法,该方法使用商用60 GHz调频连续波(FMCW)雷达传感器,该传感器专为车载应用而设计和验证。在第一阶段,使用离散小波变换(DWT)和自回归(AR)光谱分析进行粗HR估计。第二阶段使用相关向量机(RVM)方法的反向应用来细化估计,利用从第1阶段派生的窄频率窗口。最终的HR估计是通过跨时间段的顺序卡尔曼滤波(SKF)来稳定的。该系统使用安装在乘用车遮阳板上的英飞凌BGT60TR13C雷达模块来实现。在不同交通场景的真实驾驶过程中进行了广泛的数据收集。结果表明,通过Polar H10胸带验证,其HR估计的准确性可与商业可穿戴设备相媲美。与之前的工作相比,该方法具有几个优点,包括测量窗口短(5秒),在不同的照明和服装条件下操作,以及在现实驾驶环境中进行验证。从这个意义上说,该方法通过将连续生命体征感知的生物学原理转移到汽车领域的技术感官,为仿生学领域做出了贡献。未来的工作将探索传感器与视觉方法的融合,以及心率变异性(HRV)估计的潜在扩展,以进一步增强驾驶员监测系统(dms)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Biomimetics
Biomimetics Biochemistry, Genetics and Molecular Biology-Biotechnology
CiteScore
3.50
自引率
11.10%
发文量
189
审稿时长
11 weeks
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