Analysis of Brain Signals to Forecast Motor Intentions Using Artificial Intelligence

Abstract

In order to improve lifestyle of people with motor disabilities, Brain Computer Interfaces are a potential solution. BCIs seek to achieve control of a machine through the use of brain waves. In this work, a brief historical review of the state of the art in the field of BCIs is made in this work. How brain signal processing is carried out to finally obtain a BCI tool is shown. The feature extractions and the main machine learning classification methods for classifications are seen. Finally, a classification of a public EEG dataset (Physionet) is carried out to and compared with other systems as an example. Thus, showing the general aspects of the development of a BCI systems, which will be part of technologies in society 5.0.