Emotion Interaction with Virtual Reality Using Hybrid Emotion Classification Technique toward Brain Signals

Abstract

Human computer interaction (HCI) considered main aspect in virtual reality (VR) especially in the contextof emotion, where users can interact with virtual reality through their emotions and it could be expressed invirtual reality. Last decade many researchers focused on emotion classification in order to employ emotionin interaction with virtual reality, the classification will be done based on Electroencephalogram (EEG)brain signals. This paper provides a new hybrid emotion classification method by combining selfassessment,arousal valence dimension and variance of brain hemisphere activity to classify users’emotions. Self-assessment considered a standard technique used for assessing emotion, arousal valenceemotion dimension model is an emotion classifier with regards to aroused emotions and brain hemisphereactivity that classifies emotion with regards to right and left hemisphere. This method can classify humanemotions, two basic emotions is highlighted i.e. happy and sad. EEG brain signals are used to interpret theusers’ emotional. Emotion interaction is expressed by 3D model walking expression in VR. The resultsshow that the hybrid method classifies the highlighted emotions in different circumstances, and how the 3Dmodel changes its walking style according to the classified users’ emotions. Finally, the outcome isbelieved to afford new technique on classifying emotions with feedback through 3D virtual model walkingexpression.KEYWORDS3D Virtual Model, Virtual Reality, Walking, BCI, Emotion .