EEG Research Based On The Influence Of Different Types Of Music

The brain is considered to be the most complex and efficient information processing system in nature.Human beings actively explore the inside of the brain and have obtained many important research progress.Today,understanding the working mechanism of the brain is of great significance for the treatment of severe brain diseases,for the development,simulation and protection of human brain functions,and for seizing the technological commanding heights of international competition.Music also has a crucial influence on the research of EEG.As we all know,every era seems to have a preference for different types of music.Even during the day and night,the songs we listen to may not be the same.Decades of scientific research by scholars have found that the root of music preference is more deeply controlled by our brains.A study by David Greenberg,a professor of psychology at the University of Cambridge,on more than 4,000 people in the UK found that there is a clear correlation between the type of brain thinking and music preferences.This article will conduct further experiments on the influence of music on EEG signals.Analyze the effects of different types of music on attention,and conduct research on whether listening to music will increase people's attention.The main research contents of this paper are as follows:1.In this thesis we study the processing methods of EEG signals and the association between music and EEG,and proposes an experimental paradigm of the influence of music on attention.The thesis focuses on comparing the two kinds of music that are currently widely used,brainwave music and heavy metal music.The change of attention under stimulus is compared,and the two kinds of experimental results are compared with the attention under resting state.the comparison result is obtained by analyzing the characteristic parameters by constructing a brain network.2.Three analysis methods of non-stationary EEG signals are studied,time domain,frequency domain,and time-frequency analysis methods are analyzed and compared,and the shortcomings and advantages of them are summarized.Finally,independent component analysis is used in the experiment of this thesis.ICA algorithm and artifact subtraction are used to preprocess the EEG signal,and the video analysis method of wavelet transform is adopted for feature extraction.Finally,the T-test algorithm is used to analyze and verify the results.3.To study the influence of music on attention,we propose an EEG network measurement method based on graph theory,and then use phase lock value and graph theory to extract the features of the brain function network,construct the brain network and process its characteristic parameters.Look for different characteristic parameters to characterize different attention levels,so as to compare the concentration of attention under different types of music.The experimental results confirmed that when listening to brainwave music and reading books,the alpha and beta waves in the brain waves change significantly,proving that listening to this type of music can help people relax and make people more focused.On the contrary,one cannot concentrate when he(she)is in a state of heavy metal music.But compared with not listening to music,the concentration is more concentrated than in different music states.