Abstract
Functional brain imaging techniques are designed to measure the brain function for obtaining the information related to brain activity. EEG is one such technique, which measures the electric fields that are produced by the activity in the brain. Epilepsy is one of the neurological diseases that can be diagnosed by studying the EEG signals. It is a chronic disorder that causes unprovoked, recurrent seizures that affects around 50 million people worldwide. A seizure is a sudden rush of electrical activity in the brain. It is generally diagnosed if a person had at least two seizures and that were not caused by some known medical conditions. In this paper we proposed a method which is suitable for separating normal and epileptic EEG data. The combined approach of PSD, Fuzzy Entropy with Quadratic SVM has found to be very effective in such classification. The results are 96.2% accurate and it can be easily differentiated between normal person and person with epilepsy.
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