ABSTRACT



In the field of medical science, one of the major recent researches is the diagnosis of the abnormalities in brain. An EEG (Electroencephalogram) signal is a neuro signalneuro-signal which is generated due the different electrical activities in the brain. These signals can be captured and processed to get the useful information that can be used in the early detection of some mental and brain diseases. Being a non stationarynon-stationary signal, suitable analysis is essential for EEG to differentiate thebetween a normal EEG and epileptic seizures.

Epilepsy is one of the most common neurological disorders. Epilepsy is a recurrent seizure disorder caused by abnormal electrical discharges from in the brain cells, often in the cerebral cortex.

This research focusfocuses on the usefulness of EGG signal insignals for detecting seizure activities in brainwaves . Feature extraction of EEG signals is a core issue to do in brain analysis. This research proposeproposes a feature extraction technique , wavelet transform . These features have been applied to Neural Networks for classification.