Classification of healthy, inter-ictal and seizure signal using various classification techniques

Electroencephalography (EEG) is the study of brain electrical activity for different physiological state of the brain. The main purpose of this paper is to identify epileptical seizure signal from EEG signal through combinational classifier. Combinational classifier combine k-NN classifier with ANN classifier. k-NN classifier for- detection of Healthy and Inter-icial signal . then ANN classifier for the detection of Seizure signal. These three classifier works on same input values of Fractal Dimension called as Higuchi Fractal Dimension. Higuchi Fractal Dimension derived three parameters (1) Fractal Dimension, (2) Standard Deviation of Fractal Dimension and (3) Standard Deviation of scaling factor used as inputs of the k-NN classifier, ANN classifier and Combinational Classifier respectively for the classification of EEG signal and Detection of Seizure signal from EEG signal. The findings of this research on the basis of this three input statistical parameter value performance parameter like Accuracy, Sensitivity , and Selectivity calculated as 92.66%, 89% and 89% respectively and compared its performance with different statistical feature using other classifier.