Performance Analysis of Robust Local Mean Decomposition and Empirical Mode Decomposition Methods in the Detection of Epilepsy

Electroencephalography (EEG) data, which provides information about the electrical activity of brain, are widely used in diagnosis neurological diseases, EEG signals also provide important detection epilepsy, is one diseases affecting approximately 1% world’s population. In this study, it was aimed to detect epileptic seizure before by using signals. For purpose, after preprocessing steps were performed different situations from epilepsy and healthy individuals, features extracted subband obtained Robust Local Mean Decomposition (RLMD) Empirical Mode (AKA) methods. Classification studies carried out with Artificial Neural Networks (ANN). line studies, classification results states revealed performance parameters accuracy, sensitivity, specificity, precision f1 score.