A new method for predicting epilepsy seizure

In this paper I present a new method for predicting epilepsy seizure. This method depends on classification of the signal amplitudes of obtained EEG signals from healthy and non-healthy persons in different situations, like EEG signals during eyes opened and eyes closed, EEG signals from healthy and non-healthy persons during times with seizure and without seizure and from different parts of brain. This method is unique because it is new simple and promised and with it a coming seizure can be simply predicted from the small time interval before its happening. Then comparisons between the classified measurements have carried out. And finally the results were obtained. The processed signals were hundred measurements for each patient and each healthy person. The results show that this is a promised method to predict epilepsy seizure. Unfortunately this prediction of the seizure can not made long time before the seizure but only short time before it that why it waits enhancements.