A Noncontact Cardiorespiratory Monitoring System for Drivers Using Millimeter Wave Radar With Phase Continuity Tracking and Signal Quality Index
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.
Authors
- Gengqian Yang (ORCID: https://orcid.org/0000-0002-4759-4091)
- A.N. Evans (ORCID: https://orcid.org/0000-0001-8586-8295)
- Benjamin Metcalfe (ORCID: https://orcid.org/0000-0003-4279-8930)
- Robert J. Watson (ORCID: https://orcid.org/0000-0002-6596-7568)
Institutions
- University of Bath (GB)
Publication Details
- Journal
- IEEE Internet of Things Journal
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/jiot.2025.3597392
- Primary Topic
- Non-Invasive Vital Sign Monitoring
- Type
- article
- Field-Weighted Citation Impact
- 0.00