EEG-based emotion recognition of Quran listeners

In this paper, we investigate the possibility of recognizing the emotional state of a subject from his brainwave activities while he/she is listening to verses from the Quran. To this end, an experiment is designed and performed where the electroencephalogram (EEG) brain activities of 17 participants are recorded, using Emotiv EPOC neuroheadset, while they are listening to selected verses from the Quran. At the end of each trail, the participant provides a self-assessed happiness-unhappiness feedback and, at the same time, valence-arousal values are calculated from receded EEGs using fractal dimension method based on Higuchi algorithm. These values are used to train a classifier that recognizes two emotional states, happy and unhappy. The classifier is trained using random forest algorithm and the achieved recognition accuracy is 87.96%.