Brain-Computer Interface And The Single-Trial Estimation Of Its Communication Carriers

It's an ancient dream of human that using their mind to control or communicate with peripheral circumstance directly. Brain-Computer Interface (BCI) technologies revealed the scientific approaches to make the dream coming true. This novel method gives a valuable new option for individuals who cannot use conventional communication systems that depend on peripheral muscles and nerves, particularly those with neuromuscular disorders and motor disabilities. Brain computer interfaces give their users communication and control channels that do not depend on the brain's normal output channels of peripheral nerves and muscles. In last five years, BCI is becoming a hotspot and have arisen great interesting of scientists all over the world. There several BCI systems came out, among them three mental controlled keyboard had been reported. These innovatory systems achieved an average speed rate about 5~27bits/min. But there are several aspects to be improved. Firstly, the speed rate is not so high; and secondly, the flash in a low frequency may cause eye fatigue rapidly. To amend these deficient, we investigated an INR SPELLER system based on a so-called Imitating-Natural Reading (INR) paradigm. It was demonstrated that the Exogenous Given Reactions which reduce the signal-to-noise ratio were restrained and spontaneous endogenous potentials were "regularized"significantly with this novel modality. The system is expected to have a speed of 90bits/min, and to give their users comfortable conditions in using it. There are four key issues in the system, that is communication carriers, source coding, designation of virtual keyboard, and the single-trial estimation of its message carriers. The present dissertation dedicated to have a thoroughly investigation to the latter two issues. The contexts, results, and innovations of this work are as follows: 1. By investigating the BCI's origination, significance, definition, classification, feature of signals, signal processing, pattern recognition, and the development and challenges, etc., the future developments were clarified. 2. The communication carrier and coding methods were introduced. A dual-page virtual keyboard was proposed based on former works. The analytical results suggested that there are 70% higher in communication rate than the former designation target, it could up to a speed of 150bits/min, and will have a speed 5~20 times higher than the current BCIs. 3. The analysis of power spectrum of carriers in EEG showed that, the relative power have a significant change below 5Hz which could up to 15db; whereas, there were no change in the range of higher than 10Hz. The analysis gave theoretical guidelines for the following feature dimensional reducing and boosting the speed of communication. The features embedded in EEG were enhanced by means of AR model and wavelet filtering. This could improve the classification accuracy further more. we did another experiment to extract N2 components using independent component analysis (ICA). Facing the challenge of uncertainty of the polarity in ICs, a new algorithm with N2 bipolar threshold was proposed, and solved the problem. The N2 components were enhanced and made the single-trial estimation of N2 be feasible. 4. The pattern classification algorithm of support vector machine (SVM), which based on statistical learning theory, for the single-trial estimation of carriers was researched. We proposed an new SVM algorithm with AR model and ICA feature extraction. Applying the program written in Matlab6 to the data from three subjects, the effects of single-trial estimation of carriers were investigated thoroughly by means of various montages of multi channels, single-channel, difference time lengths, difference time intervals, etc. finally, a perfect results were gained by combination of P2, N2, and P3 components from two channels. The results also suggested the experiment paradigm of our mental speller is feasible.