The Identification Method And Application Of Motor Imagery EEG In Brain Computer Interface

A brain and computer interface(BCI)is a communication system that does not depend on the brain’s normal output pathways of peripheral nerves and muscles. Current interests in BCI development come mainly from the hope that this technology could be a new valuable augmentative communication option for those with severe motor disabilities that prevent them from using conventional augmentative technologies,BCI technology also has potential applications in other fields such as industry,space and defense.Motor imagery electroencephalogram(EEG) is produced by imaging limb movements without actual action. Signal processing and pattern classification are the key technology of motor imagery EEG and the BCI system.In the foundation of system researching brain signals characteristics, especially movement consciousness related of thinking information characteristics, this paper in-depth researched new method of movement consciousness information of non-intrusion extraction and recognition based on brain signals, put forward common space mode algorithm, combined with independent component analysis method to extract brain signals, for integrated support vector machine classification recognition in experiments. Experiments showed that this feature vector extracting method are very effective, faster, and easy to be fulfilled. These algorithms are suitable for the research work. It provides a new method for dyskinesia people that studying the sense of motion information on controlling prosthetic.In-depth studying, it will contribute to enhancing human brain function, promoting the development of BCI, controlled the sense of motion information on prosthesis, further expansion of BCI technology applications. The research is with important scientific significance, value and social significance.