Spectral Entropy and Vector Machines Support for Imagined Motion Detection in Brain-Computer Interfaces

Abstract

Brain-Computer Interfaces (BCI’s) aim to create a channel of communication between a person and a device without any physical action on the environment by the user. There are several BCI systems, some of them focusing on motor actions by the user. Various techniques exist for such BCI systems, such as extraction of the power in different frequency bands. These techniques have proven to be useful but require extensive training by the end user and the creation of new models every time other user intends to use the system. In this paper we present a new method based on spectral entropy to detect changes in motor area and their possible application in the detection of imagined movement. The successes obtained with this technique is about 76, %.