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

This research will use an interdisciplinary approach interfacing engineering and psychology to address the transportation safety factor of driver drowsiness. A sensing platform to non-contact monitor the physiological signals of drivers such as the electrocardiography (EKG) and Electroencephalography (EEG) will be developed to study the influence of human factors on transportation under natural driving conditions. The sensing will be based on capacitive coupling of the neural electricity under the human skin. A high sensitivity sensor and electronics will be designed to detect such bioelectricity. A newly acquired high fidelity driving simulator will be used for sensor performance validation. The performance will be evaluated by installation of the sensing device behind the driver seat and on the ceiling. The final product of this project will be an accurate sensing platform to noncontact monitor the EKG and EEG signals of the driver. This signal can then be fused with performance signals from which efficient drowsiness detection and countermeasures will be implemented. With the integration of proper data fusion algorithm, effective countermeasures can be delivered to the driver for accident prevention.