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

Jonas Brandstetter1,2, Eva-Maria Knoch1, Frank Gauterin1

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

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Summary
This summary is machine-generated.

This study introduces a novel radar-based system for contactless driver heart rate (HR) monitoring in vehicles. The method achieves accurate HR estimation, crucial for enhancing driver safety systems.

Keywords:
FMCW radarKalman filterdiscrete wavelet transformdriver monitoring systemheart rate estimationin-vehicle applicationsreal-world validationrelevance vector machinevital sign monitoring

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Area of Science:

  • Automotive Safety
  • Biomedical Engineering
  • Sensor Technology

Background:

  • Driver monitoring is vital for vehicle safety, with human factors causing most accidents.
  • Contactless heart rate (HR) measurement in vehicles is challenging due to motion and environmental factors.

Purpose of the Study:

  • To develop and validate a novel two-stage method for accurate, contactless driver HR estimation using 60 GHz FMCW radar.
  • To improve driver state assessment in real-time for advanced vehicle safety systems.

Main Methods:

  • A two-stage HR estimation approach combining discrete wavelet transform (DWT), autoregressive (AR) spectral analysis, and relevance vector machine (RVM).
  • Sequential Kalman filtering (SKF) for stabilizing HR estimates.
  • Implementation with an Infineon BGT60TR13C radar module in a vehicle's sun visor.

Main Results:

  • Robust and accurate HR estimations achieved, comparable to commercial wearable devices.
  • Successful validation against a Polar H10 chest strap during real-world driving conditions.
  • Demonstrated effectiveness with short measurement windows (5s) and under varied lighting/clothing conditions.

Conclusions:

  • The proposed radar-based system offers a viable solution for contactless driver HR monitoring in dynamic automotive environments.
  • This method advances biomimetics by applying biological vital sign perception principles to automotive sensorics.
  • Future work includes sensor fusion with visual methods and heart rate variability (HRV) estimation for enhanced driver monitoring systems (DMSs).