A Classification of Flash Evoked Potentials based on Artificial Neural Network

V. Raudonis, G. Narvydas, R. Simutis

Abstract


This paper presents how the certain sequences of the light impulses (or narrows squares) can be used to increase the number of commands for a brain-computer interface which is based on visually evoked potentials. The observation of the certain components in the power spectrum of the measured EEG will not give needed results, because the blink of the stimulators is not periodic. Therefore, different methods must be used to recognize a user commands. In this paper, a classification of flash visual evoked potentials (FVEP) of visual cortex which is induced by OFF-to-ON flash of light source based on artificial neural network is presented. The presented below results shows that is possible two classify EEG signals, which were recorded when person was visually stimulated with two type’s stimuli. Ill. 6, bibl. 11 (in Lithuanian; summaries in English, Russian, Lithuanian).


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Print ISSN: 1392-1215
Online ISSN: 2029-5731