EEG Neuro - processing for the development of neurointerfaces

Abstract Fast and accurate processing of electroencephalogram (EEG) signals is necessary for correct realization of neurointerfaces. Neural network is one of the ways of its processing. In this article the method of EEG processing with the help of multilayer perceptron trained by the algorithm of error backpropagation is considered. The results of modeling during training of the neural network showed the minimum value of the Mean Squared error.