Research On Grading Characteristics Of EEG Signal Degree Of Fear Based On VR System

In recent years,fear has been paid more and more attention by psychologists.When fear occurs,it is often accompanied by a series of physiological changes,which often lead to or cause physical illness.Fear can also cause anxiety and depression.In addition to the externalization of diseases such as tremors and convulsions,the fear is basically the emotional response of the brain to external stimuli.Therefore,the analysis of the fear EEG of normal individuals allows us to fully understand the characteristics of brain waves in fear and prevent the occurrence of various phobias.The main main work of this paper on the eigenvalue research of fear emotion grading EEG is as follows:(1)This experiment uses virtual reality technology,EEG acquisition device and Android mobile phone to form a real-time emotional evoked system.Through virtual reality technology to watch a 5 minutees fear video,innovatively put forward the application of virtual reality technology to EEG emotion induction.The combination of virtual reality technology and video stimuli better induced the fear of the subject's EEG.(2)At present,psychological questionnaires are used at home and abroad to detect phobia.Based on the subjective discomfort measure of psychology,this paper puts forward the concept of fear emotion grading,and the results of the fear emotional questionnaire survey of the subjects and EEG signals.The combination of analysis and processing,analysis and analysis of the eigenvalues of the fear emotional EEG signals,has more accurate data support than the simple psychological questionnaire survey.(3)In this thesis,LZC complexity analysis and wavelet packet transform method are used to extract feature values of fear emotional EEG.At present,the calculation of LZC complexity of EEG signals is often applied to the detection of epilepsy patients.This thesis improves the LZC complexity algorithm for the study of fear emotion EEG,and finds that the EEG signals of different levels of fear EEG are complex in LZC.The characteristics of the degree of change.The results show that the LZC values of different levels of fear emotion EEG signals are different.With the increase of fear emotion level,the LZC value of fear emotion EEG signals increases,and the possibility of phobia formation is greater.EEG signals can be decomposed into four rhythms of ?,?,?,and ?.Different rhythms represent different physiological characteristics of individuals.In this thesis wavelet packet transform is used to decompose the fear EEG signal,and the rhythm variation characteristics of different levels of fear EEG signals are studied and analy.