Smart Alert System for Driver Drowsiness Using EEG and Eyelid Movements

In the present trend suggestsdriving and navigation support systems are getting importance because it is crucial in supporting drivers in several conditions in automobile industry. It is important for driving support systems to detect the status/activity of driver’s consciousness. Detecting onset of driver fatigue could prevent the accidents caused by drowsy driving. It is proposed to detect / analyze the driver fatigue by the application of dedicated physiological indicators such as electroencephalography and also facial features such as eyelid movements based on template matching using neural network technique for closed eyes versus opened eyes. EEG signal is one of the most predictive and reliable measurements by the analysis of alpha, beta and theta band power etc, which are considered as direct factors associated with human drowsiness. The parameters such as blink duration and opening time changes reliably with increasing drowsiness.