Research And Design Of Brain Computer Interface System Based On Steady State Visual Evoked Potential

Brain-computer interface(BCI) system is a kind of real-time communication system. Through the modern signal analysis and processing technology, we can transform EEG signal into the instructions that could drive hardware equipment to implement information interaction between human brain and the outside world. Steady-state visual evoked potential(SSVEP) is widely used as based signals for BCI system due to the advantages of its high sex ratio, signal concentrated, etc.This thesis aims at the applications of SSVEP signal used in BCI system, includes a variety of EEG analysis methods, EEG experiments and ways to remove EEG artifacts. Based on MATLAB, we have made the simulation and analysis on CCA and PSDA by using SSVEP data. Finally we have designed and implemented the brain-computer interface system based on SSVEP.The SSVEP data is preprocessed by re-reference, removing baseline and filtering so as to reduce noise on EEGLAB. This thesis focuses on the application of CCA and PSDA in feature extraction of EEG signal, then verified the feasibility on identifying the target stimulus frequency by CCA and PSDA.In this thesis we use the method of PSDA and CCA for simulation analysis on MATLAB, such as feature extraction, the accuracy of algorithm and anti noise performance of the algorithm. As can be seen from the simulation results, people are more sensitive to flicker stimulation of the occipital region behind. On the other hand, the accuracy of identify the target frequency and anti noise performance by CCA is much better than that of PSDA, but its performance is affected by SSVEP data length and the number of the reference channel.Finally, several visual stimulations are achieved by Java development tools. Then we have designed an experiment on EEG acquisition by using the visual stimulation. In the application of BCI system, we have designed a system which could identify the target stimulus by mouse movement, and designed a GUI interface to realize the off-line analysis of the data based on MATLAB.