  In this paper we propose a new pre-processing technique of
Electroencephalography (EEG) signals produced by motor imagery movements. This
technique results to an accelerated determination of the imagery movement and
the command to carry it out, within the time limits imposed by the requirements
of brain-based real-time control of rehabilitation devices, making thus
feasible to drive these devices according to patient's will. Based on event
related desynchronization and synchronization (ERD/ERS) of motor imagery, the
received patient signal is first subjected to the removal of environmental,
system and interference noise which correspond to normal human activities such
as eye-blinking and cardiac motion. Next, power and energy features of the
processed signal are compared with the same features of classified signals from
an available database and the class to which the processed signal belongs, is
identified. The database classification is done off-line by using the SVM
algorithm.
