An Electroencephalography-Based Brain-Computer Interface for Emotion Regulation with Virtual Reality Neurofeedback

This is the authors' abstract. We don't add key points for this paper.

An increasing number of people fail to properly regulate their emotions for various reasons. Although brain-computer interfaces (BCIs) have shown potential in neural regulation, few effective BCI systems have been developed to assist users in emotion regulation. In this paper, we propose an electroencephalography (EEG)-based BCI for emotion regulation with virtual reality (VR) neurofeedback. Specifically, music clips with positive, neutral, or negative emotions were first presented, based on which the participants were asked to regulate their emotions. The BCI system simultaneously collected the participants' EEG signals and then assessed their emotions. Furthermore, based on the emotion recognition results, the neurofeedback was provided to participants in the form of a facial expression of a virtual pop star on a three-dimensional (3D) virtual stage. Eighteen healthy participants achieved satisfactory performance with an average accuracy of 81.1% with neurofeedback. Additionally, the average accuracy increased significantly from 65.4% at the start to 87.6% at the end of a regulation trial (a trial corresponded to a music clip). In comparison, these participants could not significantly improve the accuracy within a regulation trial without neurofeedback. The results demonstrated the effectiveness of our system and showed that VR neurofeedback played a key role during emotion regulation.