Research On The Effect Of Alpha Wave Music On Working Memory Based On EEG

Working memory(WM),which plays a vital role in human daily activities,is a memory system that temporarily stores and processes information when people are engaged in complex cognitive activities.It is a hotspot to improve WM and explore the convenient method to study on WM in many fields.The purpose of this paper is to explore the effect of Alpha Wave Music on WM and to find a systematic method to study on WM.In this paper,standard experimental paradigm and data acquisition method,effective ICA and artificial de-artifact preprocessing method were used to obtain stable WM EEG data set.In order to explore the influence of Alpha wave music stimulation on WM,wavelet decomposition was used to analyze the changes of brain frequency band and statistical method to analyze WM behavior data,from which it was found that WM was improved after Alpha wave music stimulation.In order to find a systematic method to distinguish EEG signals before and after WM enhancement,the EEG signals before and after WM enhancement were extracted and classified.The AR model features were extracted from EEG signals in WM.FPE and AIC criteria were used to select the optimal AR model order.Burg algorithm was used to solve the model coefficients,and the predictive error power of AR model was extracted as the features.It was found that the accuracy of AR model features of eight channels Fp1,Fp2,F3,F4,O1,O2,T3 and T4 can reach 83.3%,which were classified into KNN to distinguish EEG signals before and after WM enhancement,and this method is universal.The research method is a new attempt in the field of WM research,and it provides a new method and thinking for the future research on the enhancement of WM.