The Research Of EEG Processing Algorithms And Portable System

Electroencephalograph test is an auxiliary tool for clinical examination and analysis of the psychology. A good EEG test can effectively extract the various characteristics of EEG. The paper would study the status of EEG. Using different therapy, this paper would create a portable EEG signal processing system. It can not avoid the artifacts of EEG. One of the major research is about how to remove the artifacts effectively. We used the AR model to remove the artifact in this paper. The range of ERP is very low, which will be submerged in the EEG background, so it is very difficult to extract the ERP. Only by appropriate theatment, we can collect the ERP. This paper introduced the signal processing of ERP extract using the average algorithm. Through an evaluation of two experiments, we have summarized the advantages and disadvantages of the two methods.EEG is a complex and non-stationary signal. It is difficult to fully extract feature information if only traditional time-domain and frequency domain analysis of the EEG is used. Based on the review of the advantages and limitations of various theoretical basis, this paper studied Independent Component Analysis (ICA) algorithm in the treatment of brain signals. Hope that the Constrained Independent Component Analysis (cICA) algorithm can be introduced to the practical application of EEG.In this paper, a portable EEG system is not only integrated with the artifacts removed and the ERP extract but also is a portable system. The portable system design experiments to be reached at any time and in any environment.This paper EEG developed a variety of software integration method. In a real application processed EEG, prove the effectiveness of the software. It can help researchers to more accurately and fully the diagnosis and research.