Research Of Epileptic Signals Synchronization Characteristics

Synchrony is a common phenomenon in the EEG. The synchronization in different brain regional mutual effect. This will show some pathological and physiological features. Through the modeling of multichannel EEG signals and the research of synchronicity, we can have a deep understanding of the signal’s comprehensive coordination and spread between brain regions and let us deepen the understanding of the mechanism of brain dysfunction. These will have very important meaning for the diagnosis and prevention and treatment of neurological disease. This paper analyzes the phase synchronization through the average phase synchronization time matrix(APST)and phase synchronization index(PSI). This paper also design system to display the medical image.Paper’s main work are divided into the following several parts:Firstly,synchronicity analysis based on the average phase synchronization time matrix.The paper based on constructing the average phase synchronization time matrix.Using the properties of the matrix to represent the EEG signals’ s phase synchronization. This part has done much research and simulation on average phase synchronization time, the relationship of the phase difference and coupling coefficient. This part calculate the determinant of the matrix and the ln(Det)of the matrix and the quantitative analysis of the Det. Through the experiment, it show that when epileptic seizure, the value of determinant of the matrix significantly enhanced. Compared with the previous methods, using the matrix characteristics are more sensitive to the change of system characteristics and can better express the changed characteristics of EEG.Secondly,synchronicity analysis based on the phase synchronization index.The paper apply the theory of entropy to calculate the PSI of the epileptic EEG signals of different frequency. After calculate the result of PSI, we carry out the statistical analysis of PSI and done the T-Test. It can be seen from the analysis result, with the increasing frequency of epileptic EEG signals, the Phase synchronization index will gradually tend to be low. Through the T-Test, it show that the PSI can effectively distinguish between epilepsy signal and normal signal.Thirdly, system design based on the technology of Java. Swing to analyze the synchronous coupling of the EEG signals.Using Java programming to implete the phase synchronization analysis system. The system can analyze synchronicity of epileptic EEG and normal EEG signals, and display the results of the analysis. Through the experiment, it show that this system can effectively express the synchronicity characteristics of epileptic EEG and normal EEG signals. In the actual clinical brain function evaluation this system can play a supporting role.