Analyzing brain signals using decision trees: an approach based on neuroscience

Abstract

This paper presents a case study of treatment of brain signals using decision trees to classify of these signals, and they are analysed based on neuroscience. We have collected brain signals for 3 subjects during an imagination task and we classify these signals using decision trees, a supervised machine learning method. To analyse the processing data and basing in neuroscience, we have defined a matching between the electrodes position and the corresponding functions into brain. The results are promising, because we can better under-stand the brain e its functionalities.