Innovative Non-contact Sensing Platform to Prevent Traffic Accident due to Driver Drowsiness

摘要

This project conducted pilot investigations on the development of an in-vehicle measurement system that monitors the physiological signals (i.e., heart rate, heart rate variation, breathing and eye brinking) of drivers. These physiological signals will be utilized to detect the onset of driver fatigue, crucial for timely applying drowsiness countermeasures. Fatigue driving is one of the most significant factors causing traffic accidents. Clinic research has found physiological signals are good indicators of drowsiness. A conventional bioelectrical signal measurement system requires the electrodes to be in contact with human body. This not only interferes with the normal driver operation, but also is not feasible for long term monitoring purpose. This study developed a non-contact sensing platform that can remotely detect bioelectrical signals in real time. With delicate sensor electronics design, the bioelectrical signals associated with electrocardiography (ECG), breathing and eye blinking can be measured. The current sensor can detect the Electrocardiography (ECG) signals with an effective distance of up to 30 cm away from the body. It also provides sensitive measurement of physiological signals such as heart rate, breathing, eye blinking etc. The sensor performance was validated on a high fidelity driving simulator. Digital signal processing algorithms has been developed to decimate the signal noise and automate signal analyses. The characteristics of physiological signals indicative of driver fatigue, i.e., the heart rate (HR), heart rate variability (HRV), breath frequency and eye blinking frequency, can be determined. A robust drowsiness indicator will be developed by coupling the multiple physiological parameters to achieve high reliability in drowsiness detection.