Paper Title
Brain Seizure Detection and Classification using Fuzzy Logic

Epilepsy is a condition that affects a person„s brain activity. This can lead to seizures and other serious complications. The concern for a person with epilepsy is not only the seizure that are seen but those that go undetected. This is especially true for a person that may have seizure in their sleep. The goal of epilepsy treatment is to use medications and other therapies to keep a person seizure free. Another concern about seizures is the risk of sudden unexpected death in epilepsy (SUDEP).These seizures can be very dangerous and occur with different frequency and, in some cases can be very serious. Therefore automatic detection of such condition is having great importance. Electroencephalogram is one of the important tools for diagnosis and analysis of epilepsy. Electroencephalogram is the recorded representation of electrical activity produced by firing of neuron within the brain along the scalp. Thus this study proposes a method of automatic detection of epileptic seizure event by fuzzy based system and by using certain algorithm. This gives an enhanced advantage over the existing EEG based seizure detection systems due to their complex pattern classification methodologies. Keywords - EEG, Epilepsy, Seizure, Classification, Fuzzy Logic.