A Study of Familiarity Effects Classification in Human EEG Signal Using Hjorth Descriptor

Abstract

Abstract—There are a lot of researches related to human EEG signal that has been done before, but there are only a few of research related to familiarity effects in human EEG signal. Hence, this paper will classify human EEG signal while feeling familiar. This paper is using secondary data taken from DEAP: A Database for Emotion Analysis using Physiological Signals. The feature extraction method used is Hjorth Descriptor. The feature classification chosen is Coarse K-Nearest Neighbor, because the accuracy is 5.55% higher than the average of all KNN methods.

Keyword—EEG, Familiarity, Hjorth Descriptor, Coarse K-NN, K-Nearest Neighbor.