Generalized Non-Specific Seizure Based on EEG Signal Using Artificial Neural Network Method

Abstract

Abstract— Epilepsy is a seizure that occurs in the human brain. To find out, this research is to detect one of the signals in epilepsy patients, Generalized Non-Specific Seizure (GNSZ) recorded by using Electroencephalography (EEG). The dataset is a GNSZ signal taken from Temple University EEG Corpus. In this study, Hjorth Descriptor Method was used a feature extraction to process signals in time domain, where the output of this method is represented using three parameters, activity, mobility, complexity, and Artificial Neural Network (ANN) as a classification. In this study, the results of feature extraction from the GNSZ signal on the recording of EEG signals are compared with the characteristics of the normal signal. The results of this research has got 95,83% accuracy by using activity and complexity parameters. Other results obtained are GNSZ signals recognized as normal or vice versa.
Keywords—Epilepsy, GNSZ, Hjorth Descriptor, ANN