Indian Journal of Fundamental and Applied Life Sciences ISSN: 2231– 6345 (Online) An Open Access, Online International Journal Available at www.cibtech.org/sp.ed/jls/2015/01/jls.htm 2015 Vol.5 (S1), pp. 330-336/Sadeghipour et al. Research Article © Copyright 2014 | Centre for Info Bio Technology (CIBTech) 330 CLASSIFICATION OF CEREBRAL SIGNALS IN HEALTHY INDIVIDUALS AND PATIENTS WITH EPILEPSY * Ehsan Sadeghipour 1 , Kambiz Ghaemi Osgouie 2 , Ahmad Hatam 3 and Rahman Mahdizadeh 4 1 Young Researchers and Elite Club, Islamic Azad University, Bandar Abbas Branch, Bandar Abbas, Iran 2 Department of Engineering, International Campus-Kish Island, University of Tehran, Tehran, Iran 3 Department of Electrical and Computer Engineering, University of Hormozgan, Bandar Abbas, Iran 4 Sama Technical and Vocational Training College, Islamic Azad University, Bandar Abbas Branch, Bandar Abbas, Iran *Author for Correspondence ABSTRACT One of the most common neurologic disorders of the nervous system following a stroke is epilepsy from which approximately 0.6% to 0.8% of the world population suffers. This disease is caused by a sudden change in the potential difference between inside and outside of the neuron. World statistics indicate that 43 individuals per one hundred people get epilepsy in developed countries annually, while this number reaches 86 individuals in developing countries. EEG signal is the most important method to diagnose epilepsy. EEG records produce information with high lengths, and it takes a long time for the specialist to analyze the information in order to detect the epileptic area. In this paper, a variety of smart systems is used to perform automatic classifications in order to find epileptic EEG. The results indicate the superiority of classic XCS method in comparison with other ones. Keywords: EEG Signal, Epilepsy, Smart Systems, XCS INTRODUCTION One of the most common neurologic disorders of the nervous system following a stroke is epilepsy from which approximately 0.6% to 0.8% of the world population suffers. World statistics indicate that 43 individuals per one hundred people get epilepsy in developed countries annually, while this number reaches 86 individuals in developing countries (Donald, 2001). This disease is caused by a sudden change in the potential difference between inside and outside of the neuron. Normally, there is an approximate potential difference of 70 to 90 microvolts, which is due to the selective pass feature of the cell membrane, between inside and outside of the cell membrane. In this case, the brain cells are well-active, so neural waves and impulses are produced at a specific intensity and regularity. But in individuals with epilepsy, the nerve cells of some brain parts leave the natural state, and the ionic balance is disrupted among different ions inside the cell. Consequently, the potential difference changes between inside and outside of the cell, and it may change from -70 to -90 toward more negative or more positive potential. As a result of changes in ionic system, the physiological performance of the cell gets disrupted and reveals different clinical reactions. The clinical reactions caused by changes in potential difference vary based on which category of cells the changes occur in. Given this definition, it can be concluded that the neurological cell type determines the clinical symptoms of epilepsy. For example, if the changes of potential occur in the motor cortex of brain cells, then motor symptoms will reveal, and if they occur in visual, auditory, or olfactory cells, there will be some disruptions in the respective parts (Orrin, 2002). Of the most important symptoms of epilepsy, we can mention the sudden and frequent occurrence of epileptic seizure which creates problems for patients and affects the quality of their lives badly because of the limitations it causes in their social lives. Sometimes it may jeopardize their lives. Epilepsy, in the first stage, emerges through the occurrence of sudden and frequent epileptic seizures in the patient. Given the type of epilepsy, the side effects and the type of seizures vary, too. The cerebral activity observed during a seizure is mainly different from the normal state of the patient in terms of frequency and neuronal pattern. It means that the time pattern of neurons changes from the normal state into the intermediate state (pre-seizure phase) gradually and enters the state of seizure then (Iasemidis et al., 1994). Despite these