Comparing Eye-Tracking versus EEG Features for Four-Class Emotion Classification in VR Predictive Analytics

• Main Authors: Lim, Jia Zheng, James Mountstephens, Jason Teo
• Format: Article
• Language: English; English
• Published: 2020
• Subjects: T Technology (General); TA Engineering (General). Civil engineering (General)
• Online Access: https://eprints.ums.edu.my/id/eprint/25561/1/Comparing%20Eye-Tracking%20versus%20EEG%20Features%20for%20Four-Class%20Emotion%20Classification%20in%20VR%20Predictive%20Analytics.pdf; https://eprints.ums.edu.my/id/eprint/25561/2/Comparing%20Eye-Tracking%20versus%20EEG%20Features%20for%20Four-Class%20Emotion%20Classification%20in%20VR%20Predictive%20Analytics1.pdf; https://eprints.ums.edu.my/id/eprint/25561/

This paper presents a novel emotion recognition approach using electroencephalography (EEG) brainwave signals augmented with eye-tracking data in virtual reality (VR) to classify 4-quadrant circumplex model of emotions. 3600 videos are used as the stimuli to evoke user’s emotions (happy, angry, bore...