Classification of Electroencephalographic SignalsFor Brain-Computer Interface

Abstract: Brain-Computer Interface (BCI) can be used for example to help disabled people to control a computer without the use of mouse or keyboard. The brain signals beta and mu are acquired by electroencephalography (EEG) and shows what parts of the brain that are active not only at the performing of a muscular movement, but also by thinking about it. By analyzing EEG-signals with the methods linear discriminant analysis and artificial neural networks the aim is to explore which of two possible cognitive tasks a subject is performing. In the essay these methods are compared with aspect to correct classifications. In conclusion, when performing binary classification of mu and beta waves, a small multi layer perception is sufficient.