Research Of Intelligent Vehicle Control System Based On EEG And EMG And Its Obstacle Avoidance Technology

At present,there are two types of physiological signals used for Human machine interface: EEG and EMG.However,the single brain computer interface system has some shortcomings such as low signal recognition rate and unstable signal acquisition.The single EMG control interface system has the disadvantages of less action mode and limited coding.Analyze and combine the characteristics of EEG and EMG as a signal source to jointly control the terminal equipment,can integrate the merits of the two signals to make up for the lack of a single source.The forehead EEG and arm surface EMG acquisition experiments are designed in this paper.The features of the forehead EEG and arm surface EMG are analyzed.Complete the recognition of the forehead EEG during nervousness,and the recognition of the surface EMG of the ulnar extensor carpi muscle,palmaris longus muscle and biceps brachii muscle when left arm crook,left hook,and right hook are also completed.On this basis,a intelligent vehicle based on EEG and EMG control was designed to verify the control of EEG and EMG on terminal equipment.A discriminative combination of four types of EEG and EMG based on the recognition of amplitude was constructed.Vehicle movements are categorized and quantified.Four switch quantized motion command interface modes were established.In addition,the instability of physiological signals and susceptible to interference are taking into account.In order to ensure the normal operation and driving safety,the autonomous obstacle avoidance module of intelligent vehicle is designed in this paper.TTC is used as a criterion for obstacle avoidance,an offline obstacle avoidance algorithm based on BP neural network is also proposed.Finally,on-machine testing is performed on the control pattern and control method of EEG and EMG and the offline obstacle avoidance algorithm.Experiments show that the control pattern of EEG and EMG is good and effective,the recognition rate of EEG signal action reaches 91.67%,and the average recognition rate of EMG signal actions reaches more than 88.33%.The EEG and EMG signal actions respond well to the corresponding vehicle movement.The average success rate of the obstacle avoidance algorithm is 85%.In actual operation,the designed intelligent vehicle control system answers quickly,with small delay and good obstacle avoidance effect.