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Enhancing Heart Rate Detection in Vehicular Settings Using FMCW Radar and SCR-Guided Signal Processing.

Ashwini Kanakapura Sriranga1, Qian Lu1, Stewart Birrell1

  • 1Centre for Future Transport and Cities, Coventry University, Coventry CV1 2TT, UK.

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Summary

This study introduces an optimized radar system for contactless heart rate (HR) and heart rate variability (HRV) monitoring inside vehicles. The framework achieves over 90% accuracy, paving the way for advanced driver monitoring systems.

Keywords:
FMCW radarSignal-to-Clutter Ratio (SCR)contactless physiological monitoringin-cabin monitoringsignal processing

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Area of Science:

  • Automotive Engineering
  • Biomedical Signal Processing
  • Radar Systems

Background:

  • Contactless physiological monitoring is crucial for driver safety and well-being in vehicles.
  • Existing methods often require direct contact or are susceptible to motion artifacts.
  • Frequency Modulated Continuous Wave (FMCW) radar offers potential for in-cabin sensing.

Purpose of the Study:

  • To develop and optimize a signal processing framework for accurate contactless heart rate (HR) and heart rate variability (HRV) detection using FMCW radar in automotive environments.
  • To determine optimal radar placement within a vehicle for reliable physiological signal acquisition.
  • To validate the framework's performance against ground truth data and advanced sensing technologies.

Main Methods:

  • Optimized radar placement using Signal-to-Clutter Ratio (SCR) analysis with human participants in lab and driving simulator conditions.
  • Developed a processing pipeline including background subtraction, range bin selection, bandpass filtering, and phase unwrapping.
  • Integrated deep learning methods for enhanced HR and HRV extraction and benchmarking against electrocardiography (ECG).

Main Results:

  • Optimal in-vehicle radar placement was identified through SCR analysis.
  • The developed signal processing pipeline reliably extracted inter-beat intervals and heartbeat peaks without contact.
  • Radar-derived HR and HRV achieved over 90% accuracy when benchmarked against research-grade ECG, demonstrating robustness under motion conditions.

Conclusions:

  • Optimized radar positioning and advanced signal processing enable accurate, non-contact in-cabin physiological monitoring.
  • The proposed framework is a scalable solution for future intelligent vehicle and driver monitoring systems.
  • This technology enhances driver safety and comfort through continuous physiological assessment.