Design And Implementation Of The Warning System Based On EEG

With the increasing number of private cars.The problem of driving safety is becoming more and more prominent.According to the data,nearly a quarter of the cases of traffic accidents are caused by fatigue driving,so the problem of fatigue driving safety has aroused widespread concern.Aiming at the problem of fatigue driving,the design and development of a portable and efficient early warning system has become the widespread appeal of the public.In many of the characteristics of human body state discrimination,EEG is the gold standard for judging the state of the human body,and it has the advantages of objectivity and accuracy.At present,there is no efficient and portable EEG fatigue driving warning system in the market.Therefore,it is of great social significance and market value to design and develop an efficient and portable fatigue warning system based on EEG.In this paper,based on the shortcomings of the traditional EEG acquisition system,such as complex operation and poor portability,this paper has designed and implemented a portable single lead electrode based electroencephalogram acquisition system based on TGAM chip.It includes single conductor dry electrode sensor,TGAM chip and BCM417 Bluetooth module.By initializing parameters of the TGAM module and Bluetooth module and analyzing the communication protocol between modules,a portable EEG acquisition system has been successfully built.Secondly,this paper analyzes brain electrical signals and extracts the characteristic parameters related to human fatigue:attention,meditation and blink rate.The AHP model was established by means of attention and meditation,and the formula of attention and meditation was derived by using analytic hierarchy process.At the same time,the relationship between the percentage of the power spectrum density and the blink rate was obtained through the analysis,and the threshold value was obtained through experimental analysis.kNN,C4.5 and naive bayes algorithm were used to classify the correlation coefficient of attention and meditation degree and the frequency of blinking.By comparison,kNN algorithm has the best discriminant effect.At the same time,the fatiguelevel analysis model was established,and the fatigue degree of the driver was calculated.Finally,a complete EEG system is designed and developed for the portable EEG system.The software system monitors the driver's condition in real time,calculates the fatigue degree when it is fatigue,and gives the warning of classified warning according to the degree of fatigue.The feasibility of the system is verified through the function module test.This paper designs and implements a portable fatigue driving warning system based on EEG,which features high portability and high accuracy.It is of great significance to the field of fatigue safety driving.