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Abstract

Road safety remains a critical challenge, with human errors such as drowsiness and distraction as contributing factors. Physiological indicators such as Heart Rate (HR) and Respiratory Rate (RR) provide insights into understanding the driver state but are difficult to acquire in real-world driving scenarios due to the constantly changing driver pose and complex ambient environment. To tackle this challenge, a noncontact cardiorespiratory monitoring system using Frequency Modulated Continuous Wave (FMCW) radar is proposed. Unlike optical or acoustic systems, the use of radar can minimize interference from the ambient environment. However, its relatively low spatial resolution, driver motion, and variability in human Radar Cross Section (RCS) present significant signal processing challenges, especially for target tracking. To address these issues, a novel target tracking algorithm and a reference-free Signal Quality Index (SQI) based on phase continuity are proposed, aimed at significantly improving the consistency and reliability of target tracking and overall signal quality. A performance evaluation using a driving simulator and synchronized Electrocardiography (ECG) recordings for ground truth demonstrates that our proposed method achieves a mean absolute error (MAE) of 1.65 beats per minute (BPM) for HR, 0.79 respirations per minute (RPM) for RR, and a relative accuracy of 97.83 % and 95.06 %, respectively. These results highlight the potential of the proposed system to enhance driver monitoring by providing accurate and continuous HR and RR measurement, contributing to the early detection of adverse driver states.
Original languageEnglish
Pages (from-to)43480-43494
Number of pages15
JournalIEEE Internet of Things Journal
Volume12
Issue number20
Early online date11 Aug 2025
DOIs
Publication statusPublished - 15 Oct 2025

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

  • Driver monitoring
  • millimeter wave radar
  • noncontact vital sign detection
  • wireless sensing

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications

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