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Research on the Emotions Based on Brain-Computer Technology: A Bibliometric Analysis and Research Agenda

Wei Yan, Xiaoju Liu, Biaoan Shan, Xiangxian Zhang, Yi Pu

2021Frontiers in Psychology17 citationsDOIOpen Access PDF

Abstract

This study conducts a scientific analysis of 249 literature on the application of brain-computer technology in emotion research. We find that existing researches mainly focus on engineering, computer science, neurosciences neurology and psychology. PR China, United States, and Germany have the largest number of publications. Authors can be divided into four groups: real-time functional magnetic resonance imaging (rtfMRI) research group, brain-computer interface (BCI) impact factors analysis group, brain-computer music interfacing (BCMI) group, and user status research group. Clustering results can be divided into five categories, including external stimulus and event-related potential (ERP), electroencephalography (EEG), and information collection, support vector machine (SVM) and information processing, deep learning and emotion recognition, neurofeedback, and self-regulation. Based on prior researches, this study points out that individual differences, privacy risk, the extended study of BCI application scenarios and others deserve further research.

Topics & Concepts

NeurofeedbackBrain–computer interfaceElectroencephalographyInterfacingBrain researchSupport vector machineBrain activity and meditationComputer sciencePsychologyData scienceArtificial intelligenceNeuroscienceComputer hardwareEEG and Brain-Computer InterfacesFunctional Brain Connectivity StudiesNeural dynamics and brain function
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