Controlling Decisions by Head Electrical Signals

This work considers the problem of using the electroencephalogram in a real context to control devices. The proposed work takes the data from the central and parietal brain areas to perform a steady state visually evoked potentials (SSVEP)-based Brain Computer Interface (BCI) model. The BCI output was retrieved by the human head electrical activity within a scenario that requires participants to think about a predefined image. The simulations were performed by 7 healthy participants 5 men and 2 women between 23 and 56 years old. A system composed by a Neural Network has been applied to develop the predictive model. The model developed can predict the human thinking with an accuracy more than 70% in the validation set for each participant.