The Analysis Method For Localizing The Sources Of Electroencephalogram Based On The Data Of Spatio-Temporal

Estimating the electric current sources within the brain from electroencephalographic (EEG) recordings is called the inverse problem of EEG, This research is involving the subjects such as informatics, calculation electromagnetic field theory and biomedicine engineering etc.The research will possess the important effect at the aspects such as neuropathy diagnosis, exploring the feeling of man and cognition course etc. In this paper, the methods for solving the EEG inverse problem based on the data of spatio-temporal are investigated in details and the research work is focused on the following several aspects:Firstly, the solution of forward problem under different models is discussed .based on simplified asymmetrical concentric four-sphere model, an emulate calculation on the forward problem of EEG was made.Secondly, the commonly used algorithm for the inverse problem of EEG is analyzed.Based on simplified asymmetrical concentric four-sphere model and STSM,the MUSIC algorithm are mainly investigated.This algorithm is the directly established in the section of observation records,so it makes good use of the information of the time domain and the space domain. The MUSIC algorithm can locate multiple dipolar source by scanning a single-dipole model through the whole volume.The calculate complexity of this algorithm is much less than the multidimensional nonlinear algorithm. At last, in order to solve the problem that the MUSIC algorithm is sensitive to color noise and failed in identifying synchronously active sources, an improved algorithm is proposed.Using the different correlation time delay between the noise and the desired signal to depress the spatial coherence noise. Using independent topographies and recursive algorithm to find the synchronous sources.Emulate experiment by simulated data shows good performance on depressing the spatial coherence noise and finding the synchronous sources.