Classifying motor imagery with FES induced EEG patterns
Functional Electrical Stimulation (FES) is commonly used in motor rehabilitation. Also, motor imagery (MI) based brain computer interfaces (BCIs) have been proposed as a possible treatment by activation of the same brain areas as the ones involved in visuomotor tasks. However, to use a MI-based BCI it is necessary to perform a screening session to compute a classifier. In this work we study whether it is possible to setup a classifier with brain patterns induced by FES signals and classify MI data.