Study on Brain Computer Interface based on Motor Imagery

Directly from the brain thinking activity signals to communicate with the outside world, to achieve the heart and heart communication, achieve control of the surrounding environment, even is the dream of human beings since the ancient times is the pursuit of. Brain-computer Interface (Brian Computer Interface: BCI) this novel human-computer interaction mode provides the scientific way to realize this dream. People hope that the new communication technology can be used in traffic tools, weapons, and other auxiliary control system, especially for those neuromuscular damage, cannot use the conventional methods of communication disability patients provides another way to communicate with the outside world. Exercise imagination refers to through the brain consciously simulate a certain action, but without obvious physical activity. In the human brain has a corresponding motor cortex area, when people have limbs activities, the motor cortex area is active. In imagine movement, although physical activity, but has remained active in the areas of the brain's corresponding motor cortex, the brain also sends out the corresponding EEG signals, so that there will be movement similar brain electrical signal, but due to the body don't exercise, avoid the my electricity interference, using the movement of the thought mainly, participants imagine left and right hand movement, or don't want to, the need to constantly training, participants learn to imagine the essence of sport, to avoid other distractions. So-called brain-computer interface, it is an organization that does not depend on peripheral nerves and muscles, etc. Usually the brain output channel of communication system. In recent five years, the research of this field gradually formed a hotspot; dozens of research team in the world have developed various forms of BCI experiment system. This research mainly based on multiple electrodes EEG recording, for a variety of brain stimulation mode is intended to explore the spatial and temporal variations of electrical signals. Applied to the second-order blind identification, phase synchronization and energy entropy of the signal analysis methods to analyze imagine movement EEG signals processing, extracting its features, and USES the BP neural network and support vector machine (SVM) classification method for different types of EEG classification is imagine movement, won a higher classification accuracy and designed a BCI system based on motion imagination, through this system, participants can more freely to imagine to control the mouse movement or virtual car movement to the left or right. The innovation of this study is to imagine the movement of brain electrical signal as input signal of the brain-computer interface system, imagination is a very complicated process, and the brain electrical signal characteristic is not obvious, so higher requirements for feature extraction and classification algorithm.