Research on Algorithm for Feature Extraction and Classification of Motor Imagery EEG Signals

Abstract

This paper made a research on the feature extraction and pattern recognition of left and right hands motor imagery EEG signals. In combination with the data from BCI Competition III, denoising preprocessing is carried out for EEG signals firstly; and then, the relative wavelet energy is extracted as a feature vector from the Channels C3 and C4 by use of the algorithm for relative wavelet energy, and pattern recognition is carried out by use of the radial basis function neural network (RBFNN). Simulation results show that the proposed method achieves good classification results.