Human emotions classification and EEG channel reduction: A review

Abstract

Brain signals are collected from the human scalp through a set of electrodes placed over the entire scalp. In recent years, the researchers are using higher number of Electroencephalography (EEG) channels to collect the brain signal activity to develop Human Computer Interface (HCI) or Brain Computer Interface (BCI) systems. Using larger number of electrodes gives higher accuracy at the cost of losing lesser computational time, higher memory requirement and increasing subject burden. In order to overcome this problem, a channel reduction algorithm is proposed for reducing the number of active channels without reducing the performance of the systems. The key idea behind this channel reduction is lies on finding the brain region or common brain region which act as emotional centre for assessing all different types of emotional activity of human. Therefore, a reduction to a number of channels which carry the same information with less time for computing and feature extraction is necessary.