— Driver’s psychosomatic state adaptive driving support safety system is highly expected to reduce the number of traffic accidents. Drowsiness is thought as crucial risk factor which may result in severer traffic accidents. When a driver is fallen in a drowsy state, it influence may appear in fluctuating of heart beat and eye movement. Heart rate was acquired from Electrocardiogram (ECG). Then heart rate variability (HRV) was calculated from ECG waveform using the maximum entropy method. CCD camera with infrared ray was introduced to capture gaze direction and eyelid closure. This study took a hypothesis that simultaneous measurement of both heart rate variability (HRV) and blinking duration may be useful means to detect onset of drowsiness in real time. The method to estimate onset of drowsiness was proposed, which function may be incorporated into driver’s psychosomatic state adoptive driving support safety system for the reduction of traffic accidents.
— Psychosomatic state, driver monitoring, onset of drowsiness, blinking duration, heart rate variability.
Masahiro Miyaji is with the Institute of Information Science and Technology, Aichi Prefectural University, Nagakute-shi, Aichi-ken, 480-1198, Japan (e-mail: email@example.com).
Cite: Masahiro Miyaji, " Method of Drowsy State Detection for Driver Monitoring Function," International Journal of Information and Electronics Engineering vol. 4, no. 4, pp. 264-268, 2014.