Estimulación visual basada en conceptos y su análisis mediante electroencefalografía

This article is oriented towards verifying the performance of a computational algorithm capable of automatically identifying the discriminating characteristics or traits generated by brain waves using electroencephalographic (EEG) readings, when the human being perceives concepts through a set of visual stimuli, which are related to the process of human communication. A comparison and study of the existing works in the literature related to the subject exposed, and the limitations found in current research are carried out. A methodology for the treatment of EEG signals is developed, the preprocessing of the signals is carried out through the implementation of a precise and efficient digital filter type FIR of order 4 to eliminate signal noise. The Independent Component Analysis (ICA) method is implemented for the elimination of artifacts present in the signals, and later they are divided into epochs to analyze their behavior through event-related potentials (ERP). Finally, the signals that generate different concepts presented through pictograms are analyzed and the observations are reported, where it is denoted that the algorithm developed is functional for the extraction of parameters for the different categories of concepts.