%0 Journal Article %T NUMBER RECOGNITION SYSTEM USING ELECTROENCEPHALOGRAM (EEG) SIGNALS %A £¿Shashibala Rao %A Bharti Gawali %A Mehrotra S.C. %A Pramod Rokade and Rakesh Deore %J Advances in Computational Research %D 2012 %I Bioinfo Publications %X This paper focuses on number recognition from feature extracted using Electroencephalogram (EEG) readings. EEG signals were recorded at Department of Computer Science and IT, Dr. B. A. M. University, India, from 6 volunteer subjects. A random number generator Graphics User Interface was developed in VB7. It is used to display numbers from 0 to 9 which worked as Visually Evoked Potential (VEP) for the experiment. The database of 6 male right-handed subjects in the age group of (20-25) was created and used as training data set. By exposing the same set of subjects to the GUI again, new EEG recordings were collected. This new set of EEG readings was considered as testing data set. The testing data was searched and matched with trained data set for recognizing pattern of each number. The experiments were conducted by concentrating on Beta signal and Linear discriminate analysis (LDA) was implemented to classify the data. The recognition rate observed was different for different numbers. Overall recognition rate observed was 68.33%. It is also seen that there exist a unique pattern for each number. %K Beta signals %K EEG %K GUI random number generator %K VEP %K LDA %K recognition rate. %U http://bioinfopublication.org/viewhtml.php?artid=BIA0000291