The Research Of Comprehensive Evaluation Index Of Driving Fatigue Based On EEG And Cerebral Flow

With the consistent development of scientific technology and national economy, the inventory of cars in our country increases as well. Nevertheless, the incident of serious traffic accidents increases year after year while cars do bring convenience to people in daily lives. It is no doubt that one of the most important causes of accidents is fatigue from the driving. Therefore, how to monitor the fatigue state effectively and offer the alert to the driver has become the most important question of decreasing incident of accidents. This paper uses simulation experiment of fatigue driving to study the fatigue driving process based on the comprehensive index of EEG and cerebral flow. Aiming at the EEG using Hilbert-Huang Transform to extract features, the paper puts forward the judgment based on the EEG and cerebral flow, and analyses briefly the correlation of EEG and cerebral flow under the state of fatigue.The research contents included:Collecting the EEG from human brain top, occipita and temporal before and after fatigue driving. Analyzing EEG using Empirical Mode Decomposition and Hilbert transform and archiving Hilbert Marginal spectra from different states of driving; studying the variation of α band EGG before and after fatigue driving and comparing the ease effect between the massage device and relaxation with nature.Measuring the mean flew velocity of cerebral artery using Intracranial Doppler ultrasound measurement instrument, and exacting the regular pattern before and after fatigue driving. Comparing the influence between two kinds of massage at the same time.Studying the correlation between EEG and cerebral flew and finding out the close correlation between artery signal measured by temporal window and EGG measured by T3and T4. Calculating the cerebral energy parameter and analyzing energy parameter which can reflect changes in brain before and after fatigue driving.Analyzing the multiple physiological indexes and extracting the comprehensive evaluation indexes which effectively contain original physical signal of fatigue driving. Judging the extracted indexes using cluster analysis and inspecting whether it can recognize the state of fatigue driving or not.