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.
Highlights
Brain-Computer Interface (BCI) is a short form of the interface between brain and computer. It reflects the consciousness of people through the EEG signals but not the normal physiological output pathways constituted by peripheral nerves and muscles, so it is a new way of communication and control [1]
The research on BCI projects based on motor imagery EEG signals was firstly carried out by Pfurtscheller et al The result showed that, during unilateral limb movement or motor imagery, Event related desynchronization(ERD) was produced in the contralateral brain areas and event related synchronization (ERS)[2] was produced in the ipsilateral brain area
During the experiment, the cerebral cortex where channels C3 and C4 were located represented the area of right and left hands motor imagery in the brain; during the motor imagery, ERD/ERS in the areas on both sides of the brain was symmetrical, i.e., during the right hand motor imagery, ERD occurred on the cerebral cortex for motor imagery in the left area of the brain while ERS occurred on the cerebral cortex in the right area of the brain; and vice versa
Summary
Brain-Computer Interface (BCI) is a short form of the interface between brain and computer It reflects the consciousness of people through the EEG signals but not the normal physiological output pathways constituted by peripheral nerves and muscles, so it is a new way of communication and control [1]. The research on BCI projects based on motor imagery EEG signals was firstly carried out by Pfurtscheller et al The result showed that, during unilateral limb movement or motor imagery, Event related desynchronization(ERD) was produced in the contralateral brain areas and event related synchronization (ERS)[2] was produced in the ipsilateral brain area. Neural network, taking the ERD/ERS phenomena corresponding to left and right hands motor imagery as the differentiating criteria in combination with the characteristics
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