Research On Brain-computer Interface System Based On Steady-state Visual Evoked Potential

BC（IBrain-Computer Interface）technology is a new communication and controltechnology which could achieve the goal to directly control external devices throughthe brain or communicate with the external environment without relying on thenormal human output information. Research on the human brain and the developmentof digital processing technology promote the BCI to be one of the hot spots of thenational research.Recently, Brain-Computer Interface technology based on the Steady-state visualevoked potential receive widespread concern of the research scholars as it has highreliability and stability, what’s more, it is relatively simple to implement. Currently,most of the research of Brain-Computer Interface technology stay in the theory stateas the real-time performance and stability of the BCI technology has been the majorproblem to hinder its practical application. This manuscript designed aBrain-Computer Interface system based on the SSVEP after a comprehensiveresearch on the character of SSVEP signal and an idle detection algorithm based onCCA has been proposed which could be used in the BCI system to realize the humanbrain to control mouse. We have also verified the stability and real-time of theproposed system. The main contents of this paper include following aspects:(1) Based on the analysis on related research, this manuscript described thesignal character of EEG signal and the generation mechanism of the steady-statevisual evoked potential signal. Due to induce stable SSVEP signals need some visualsimulation to satisfy certain conditions, this paper launched comparative study aboutthe impacts on the SSVEP signal from frequency of visual simulation, color and dutycycle. Then, the LCD visual stimulation and the LED visual were designed. Finally,the overall design of software was described; moreover, the BCI software systembased on SSVEP was realized.(2) Based on the spectrum distribution characteristics of SSVEP signals underdifferent duty flash stimulation, a SSVEP signal extraction and classification methodswith idle detection function was proposed to improve the usefulness and accuracy ofthe system.(3) The BCI system application testing platform based on the SSVEP was build,targeting the mouse as the actual control goal, and then, the test was conducted while the test result show that the system has better real-time and stability.The SSVEP based BCI system proposed in this paper could effectively translatethe SSVEP signal into the control commands, realizing the goal to use SSVEP signalto control the external devices. This system could be applied to the paraplegic patientrelated auxiliary equipment development and other areas of life.