Abstract:
This paper presents a real-time Electro-
Encephalogram (EEG) identification system with the goal of
achieving hands free control. With two EEG electrodes placed
on the scalp of the user, EEG signals are amplified and digitised
directly using a ProComp+ encoder and transferred to the
host computer through the RS232 interface. Using a real-time
multilayer neural network, the actual classification for the
control of a powered wheelchair has a very fast response. It
can detect changes in the user’s thought pattern in 1 second.
Using only two EEG electrodes at positions O1 and C4 the
system can classify three mental commands (forward, left and
right) with an accuracy of more than 79%.
