EEG Analysis Based On Partial Phase Synchronization And Partial Recurrence Synchronization

EEG reflects the activity of neurons in the human body, which contains very important information, which not only allows us to have a better understanding of the human brain, but also to help doctors diagnose and treat brain disorders. What’s more, through the better understanding of human brain we can tap the potential of human brain. Therefore, the analysis of EEG is of great significance. In this paper, we apply two new methods to analyze EEG based on previous work, the following is three specific research work:Firstly, middle-aged EEG and teenage EEG analysis based on partial phase synchronization.This paper applies a new approach based on partial phase synchronization to calculate the degree of coupling between two channels of EEG. Compared to the traditional method of phase synchronization, it can effectively eliminate the interference of other channel EEG. Applying this method to middle-aged EEG and teenage EEG, experiment shows that coupling strength of teenage EEG is weaker than middle-aged EEG which consistent with the real world.Secondly, normal EEG and epilepsy EEG analysis based on partial phase synchronization.The paper applying partial phase synchronization to normal EEG and epilepsy EEG, experiment result reveals that coupling strength of epilepsy EEG is greater than normal EEG which indicates that the partial phase synchronization index can be an indicator to distinguish normal EEG from epilepsy EEG.Thirdly, normal EEG and epilepsy EEG analysis based on partial recurrence synchronization.As EEG exhibits multiple time scales, the method applied above can not calculate phase directly. Partial recurrence synchronization analysis can solve the problem. In this paper, applying partial recurrence synchronization to analyze normal EEG and epilepsy EEG, we can conclude that coupling strength of epilepsy EEG is greater than normal EEG. In another word, the partial recurrence synchronization index can also be a reference to tell normal EEG from epilepsy EEG.