Analysis of Frequency Bands and Channels Configuration for Detecting Intention of Change Direction Through EEG

The design of solid interfaces based on the patterns of brain activity that underlie human decision-making are a field of interest in creating interfaces that allow recover the pathway between the brain and the muscular system to be rectified. In this work, a Brain Machine Interface is presented to detect the user's intention through the differentiation of the EEG signals into two classes according to their temporal and frequency characteristics, comparing different electrodes configurations. The better band for all the configuration seems to be Theta (4–7 Hz) from a centralize sensorimotor area, which obtained 69 and 70% accuracy results for two subjects.