Eeg signals classification: motor imagery to control a robotic manipulator

Abstract

In contemporary society, there is an increase in the number of people with some type of motor disability, which can make it impossible to perform simple daily tasks such as walking or picking up an object. Activities related to limbs control of a human being are mainly associated with nervous system, which affected by some trauma or degenerative disease can disable neural commands transmission. However, by reading electroencephalogram (EEG) signals, it is possible to digitally direct them to their destination. This article seeks to present a computational model capable of controlling a robotic manipulator through EEG signals to move it along in axes: x, y and z. At the end, the proposed model efficiency and performance will be evaluated.