Analysis of Brain Signal for the Detection of Epileptic Seizure

ABSTRACT The electroencephalogram (EEG) signal is very important in the diagnosis of epileptic seizure. Long-term EEG recordings of an epileptic patient contain a huge amount of EEG data. The detection of epileptic activity is, therefore, a very demanding process that requires a detailed analysis of the entire length of the EEG data, usually performed by an expert. This paper describes a classification of EEG signals for the detection of epileptic seizures using high pass filter and comparing the results with low pass filter through Matlab software. The proposed methodology was applied on EEG data sets that belong to three epileptic subjects during a seizure. The results confirmed that the proposed algorithm has a potential in the classification of EEG signals and detection of epileptic seizures, and could thus further improve the diagnosis of epilepsy.