Study On The Brain-computer Interface System Of Left-right Hand Motor Imagery

Brain-computer interface (BCI) is a novel kind of human computer interface being explored since last decade. BCI gives their users communication and control channels that does not depend on the brain's normal output pathways of peripheral nerves and muscles. It supplies the paralyzed patients with a totally new approach to communicate with the environment. The electroencephalogram (EEG) based method is the main interest of current BCI research due to its advantages of low cost, convenient operation and non-invasiveness. Design and implementation of an online system plays an important role in BCI research with the purpose of producing practical devices for real-life clinical application. Compared with offline data analysis, an online BCI has great difficulties in fulfilling real-time processing, system practicability and brain-machine co-adaptation.Based on the knowledge of national and international BCI development, the work for this paper systematically studied a BCI that was based on the left-right hand motor imagery. It discussed both offline problems and real-time online problems, and made several improvements.The realization of Brain-Computer Interface(BCI) based on motor imaging under LabVIEW is presented in this paper. The critical parts of the solution are the realization of the visual stimulation and the feature extraction of EEG. The system of motor imagery BCI based on left and right hand is set up using one computer and the Active One Biopotential Measurement System developed newly. The scalp electrodes are used for detection of motor imagery potentials. It is noninvasive and can be accepted easily.For one thing, the visual stimulation of BCI is designed through LabVIEW software programming. The shuffle of left and right hand images represent motor imagery stimulation of different physical. The testee fixate on playback images of the left and right hand on the screen, which can be distinguished imagined limbs through the analysis of EEG generated by the testee. For another, the filtering method is used to improve the Signal-to-Noise Ratio(SNR). Interception of EEG data, which intercept with the sliding window has been analyzed from the perspective of time-domain energy and obtained the feature extraction of motor imaging EEG. On-line feature extraction lay the foundation for the realization of real-time system. The program can effectively extract the features of motor imagery, and effectively classify by off-line pattern recognition, classification results achieved by 82%.In this paper, motor imagery EEG based on left and right hand processing and recognition was discussed and analyzed, and it builds contribution to promote the classification performance and generalization ability of BCI system and has reference value for realizing online BCI.