Identificação de atividades cognitivas a partir de modelos de aprendizado de máquina aplicados ao processamento de sinais de Eletroencefalograma (EEG)

Abstract

The different types of activities performed by the subject, such as reading; lis- ten to music; to dance; among others, they lead to the activation of brain regions.

Among these activities, cognitive activities are associated with an activation of brain

regions related to learning, such as the frontal lobe regions (Superior Frontal, Pre- cuneus, among others). Several studies have been developed to relate cognitive

activities and associated brain regions. This type of study is important in unders- tanding the functionality and connectivity of the brain and this knowledge can help

to diagnose abnormalities in its functioning. This study aims to develop a classifier model of brain activities during the development of a cognitive activity within the three categories of activity: Video game, music or mathematics. For this, we used the Electroencephalogram (EEG) signals collected in two public databases and using the technique of estimation of brain sources, the anatomical regions related to each

of the activities were estimated. After this determination, a model based on ma- chine learning was trained and tested that classifies the type of activity performed

according to the activity categories. From the obtained results, we can highlight the en-cephalic activities classifier model elaborated with an accuracy of 99.9%.