Classification of Direction perception EEG Based on PCA-SVM

In this paper, an experiment was designed to get the electroencephalography (EEG) when people caught the vision of moving to different direction (right, left, front, back). Through Fourier Transform., the feature of the EEG was obtained. Then, the algorithm of principal component analysis (PCA) was used to simplify the feature. Finally, in order to classify the direction perception EEG, it was distinguished by the feature with support vector machine (SVM). Result proved that the classification of direction perception EEG was feasible.