Independent Component Analysis And Its Brain - Computer Interface Technology

Brain-computer Interface (BCI) is a communication system that connects brain and computer or other electric equipment. The character of BCI is that it can make a person communicate with the outside world without depending on peripheral nerves and muscle's normal output channels. For this reason, scientists and medical experts in related fields take electroencephalographic signal's bioelectricity changes as input signal of BCI, which is taken on the condition of all kinds of environment, to improve standard of living of the sufferer.The BCI system consists of signal input, processing, exchanging and output. Processing and exchanging algorithms are the most important parts in BCI technology. The purpose of signal processing is to extract the hidden or weak patterns that probably have some physiological and psycho physiological significance from EEG signals in sophisticated noise background and then apply them to the research on clinical or cognitive science.The traditional methods for removing artifacts are based on time or frequency analysis. But due to the strong randomness and nonstationarity of EEG, the results obtained from those traditional methods are not very satisfactory. Independent component analysis method developed in the 90's of the 20th century is a multi-dimensional statistical analysis method. It is used to analyze the mutually independent nongaussian signals. When some certain assumptions are satisfied, ICA can effectively separate the independent source signals from the synchronous multichannel recording, and then according to some independent sources, we can further analyze their physiological significance.In this paper, we will make an in-depth study on the basic theory, algorithm...