The Experimental Study On Visual Evoked Potential Based Brain-Computer Interface

Brain-computer interface (BCI) is a novel kind of human computer interface being explored since last decade. BCIs give their users communication and control channels that do not depend on the brain's normal output channels 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. BCI research has drawn attention of scientists in the brain-science research, rehabilitation engineering, biomedical engineering and human machine automatic control. However, BCI technology is still under development. Current BCIs have relatively low communication speed and may become unstable sometimes. Experimental study has been carried out to develop the visual evoked potential (VEP) based brain-computer interface. VEP is the evoked response elicited by the specific visual stimuli, which occur at specific time and specific location, is relatively easy to be detected and recognized. VEP may be used for the brain-computer interface as long as the user's vision is right. Users require little or no training for using it.Studies have been carried on the in the steady-state VEP based BCI. Due to the limitations of the steady-state VEP based BCI, a new method that using the transient VEP for BCI was first proposed and developed in this study. It is a supplement to the existing VEP based BCI technologies. The principle of the VEP based BCI was explained upon vision physiological characteristics of human. Multiple visual stimulation patterns were produced on the computer screen through programming. Several flickering blocks on the screen were adopted to represent a number of possible selections. The subject may choose one just by fixating at one of the blocks for a short time. A new technique that called the complex stimulation of the same frequency method was also developed in the current work. It can improve stimulation efficiency when there are several visual stimulation modules on the screen, which is especially suitable for the transient visual evoked potential based BCI.A VEP based BCI experimental system was set up using two computers and the Active One biopotential measurement system. The scalp electrodes were used for detection of VEPs in the occiput. It is noninvasive and can be accepted easily. Wavelet transform has been studied here to extract the poor VEP signal from strong noises. A wavelet time-frequency filter was designed according to different time-frequency characteristics of VEP and noises. Combining with averaging method, the wavelet filter could improve signal/noise ratio effectively. Experiment results showed that only 9-25 trials are needed to extract the VEP signal with distinguishable features, which may improve the communication accuracy and speed of brain-computer interface. The method for extracting feature vectors in the wavelet transform domain was proposed. Experiments show that it can effectively extract VEP features, decrease noises and reduce the dimensionality at the same time. Three methods for translating BCI control signal were developed. They are (1) the signal recognition algorithm based time domain features;(2) the linear discriminant analysis based on dot product of feature vectors;(3) the VEP fuzzy recognition algorithm based on neural network.Experiments showed that the feature vector extracting from the wavelet transform domain and the VEP fuzzy recognition algorithm based on neural network are very effective and easy to be fulfilled. These algorithms are suitable for the research work. Visual stimulation experiments on the color, size and flickering frequency of the stimulation module have been conducted. Useful results, which are valuable to design BCI visual stimulators, were achieved based on the experimental work and theoretical...