BCI (called Brain-Computer Interface) is an interface that allows direct communication between human brain and an
external device. It bases on EEG signal collection, processing and classification. In this paper a complete BCI system is
presented which classifies EEG signal using artificial neural networks. For this purpose we used a multi-layered
perceptron architecture trained with the RProp algorithm. Furthermore a simple multi-threaded method for automatic
network structure optimizing was shown. We presented the results of our system in the opening and closing eyes
recognition task. We also showed how our system could be used for controlling devices basing on imaginary hand
movements.
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