METHOD OF CLASSIFICATION OF ELECTROENCEPHALOGRAPHIC SIGNALS IN INTERFACE BRAIN-COMPUTER

摘要

FIELD: medicine.;SUBSTANCE: invention relates to field of human brain communication with computer and is intended for EEG registration, analysis and interpretation of brain signals for controlling external execution units. From EEG signal isolated are positive maximums of amplitude of EEG signals from all deviations. If values of two neighbouring positive peaks differ by less than threshold of human psychophysiological perception, they are considered equal and the second peak is excludes from further analysis. Simultaneously with isolation of the first positive peak from support deviation values of amplitudes of EEG signals by all remaining deviations are registered. In teaching multilayer neural network (MNN) additionally formed is array of indices of classes of mental movements, performed by user, who represents outlet array for MNN teaching, weighting coefficients of classification by back-propagation algorithm are calculated. In identification of mental movement array of inlet vectors is supplied to MNN for calculation of outlet vector, used for determination of user's mental movement class.;EFFECT: method makes it possible to reduce time of mental command identification and simultaneously increases accuracy of their identification.;2 cl, 20 dwg, 4 tbl