Technology Of Brain-Computer Interface Based On Spontaneous Eeg And Research On Recognition Methods Of Eeg Signal

A brain–computer interface (BCI) is a communication system that does not depend on the brain's normal output pathways of peripheral nerves and muscles. It is an alternative and a novel interface between human and computers. The essence of a BCI is to deduce human thoughts or intentions via electroencephalogram (EEG) signal and so to realize the communication between human and computers. A BCI is not only an important way to understand and improve brain functions but also a novel communication and control mode. A BCI is expected to improve the human living level. It has wide application prospect in many areas such as rehabilitation for disabled people, assistant control for normal people, entertainments, brain cognization, etc.BCIs include two kinds, one is BCIs based on spontaneous EEG and the other is BCIs based on evoked EEG. BCIs based on spontaneous EEG depend on spontaneous EEG signal. Firstly, spontaneous EEG signal is produced by human specific thoughts. Then, the spontaneous EEG is recorded through an acquisition system of biosignal with high performance. The recorded EEG signals are extracted features on real-time with the disigned data processiing algorithm. The signal is classified automatically and so human thought status is determined. Finally, the thought status is translated into the predefined control command. So the BCI realizes the communication between human brain and computers or the direct control to other external devices with human brain. This dissertation researched some technologies BCIs based on spontaneous EEG and recognition methods of EEG signals. Firstly, some technologies were analyzed and discussed. A BCI system was designed on these technologies. And then pattern recognition methods among these technologies were studied deeply. Finally, an experimental paradigm based on motor imagery was designed according to established experiment system and the obtained experiment data were used to verify these pattern recognition methods.