Physiological Driver Monitoring Using Capacitively Coupled and Radar Sensors

Applied Sciences

IvanD. Castro¹  Chris Van Hoof¹  Robert Puers¹  Aakash Patel²  Tom Torfs²  Marco Mercuri³ 

[1] KU Leuven, Department of Electrical Engineering - ESAT, 3001 Leuven, Belgium;imec Belgium, 3001 Leuven, Belgium;imec The Netherlands/Holst Centre, 5656 AE Eindhoven, The Netherlands;

关键词: advanced driver assistance systems;    capacitively-coupled ECG;    contactless driver monitoring;    heartbeat;    radar remote sensing;    respiration;    unobtrusive health monitoring;    vibration compensation;    vital signs monitoring;   

DOI  :  10.3390/app9193994

来源: DOAJ

【 摘 要 】

Unobtrusive monitoring of drivers’ physiological parameters is a topic gaining interest, potentially allowing to improve the performance of safety systems to prevent accidents, as well as to improve the driver’s experience or provide health-related services. In this article, two unobtrusive sensing techniques are evaluated: capacitively coupled sensing of the electrocardiogram and respiration, and radar-based sensing of heartbeat and respiration. A challenge for use of these techniques in vehicles are the vibrations and other disturbances that occur in vehicles to which they are inherently more sensitive than contact-based sensors. In this work, optimized sensor architectures and signal processing techniques are proposed that significantly improve the robustness to artefacts. Experimental results, conducted under real driving conditions on public roads, demonstrate the feasibility of the proposed approach. R peak sensitivities and positive predictivities higher than 98% both in highway and city traffic, heart rate mean absolute error of 1.02 bpm resp. 2.06 bpm in highway and city traffic and individual beat R-R interval 95% percentile error within ±27.3 ms are demonstrated. The radar experimental results show that respiration can be measured while driving and heartbeat can be recovered from vibration noise using an accelerometer-based motion reduction algorithm.

【 授权许可】

Unknown