Analysis of EEG Signals for Brain Computer Interface
Jessy Parokaran, Ali Ozgur Argunsah, Baran Curuklu, and Müjdat Çetin
Swedish Association of Medical Engineering and Physics, Medical Technology Days,, Vasteras, Sweden, September 2009
dvancements in biomedical signal processing techniques have led Electroencephalography (EEG) signals to be more widely used in the diagnosis of brain diseases and in the field of Brain Computer Interface (BCI). BCI is an interfacing system that uses electrical signals from the brain (EEG) as an input to control other devices such as a computer, wheel chair, robotic arm etc. The aim of this work is to analyse the EEG data to see how humans can control machines using their thoughts.
In this paper we studied the reactivity of EEG rhythms in association with normal, voluntary and imagery of hand movements using EEGLAB, a signal processing toolbox running under MATLAB. In awake people, primary sensory or motor cortical areas often display 8-12 Hz EEG activity called mu rythm when they are not engaged in processing sensory input or produce motor output. Movement or preparation of movement is typically accompanied by a decrease in this mu rhythm called 'event-related desynchronization'. A