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基于脑机技术的情绪研究:文献计量分析与研究议程

Research on the Emotions Based on BrainComputer Technology: A Bibliometric Analysis and Research Agenda.

作者信息

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

机构信息

School of Management, Jilin University, Changchun, China.

出版信息

Front Psychol. 2021 Nov 1;12:771591. doi: 10.3389/fpsyg.2021.771591. eCollection 2021.

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.

摘要

本研究对249篇关于脑机技术在情感研究中应用的文献进行了科学分析。我们发现,现有研究主要集中在工程学、计算机科学、神经科学、神经病学和心理学领域。中国、美国和德国的出版物数量最多。作者可分为四组:实时功能磁共振成像(rtfMRI)研究组、脑机接口(BCI)影响因素分析组、脑机音乐接口(BCMI)组和用户状态研究组。聚类结果可分为五类,包括外部刺激与事件相关电位(ERP)、脑电图(EEG)与信息采集、支持向量机(SVM)与信息处理、深度学习与情感识别、神经反馈与自我调节。基于先前的研究,本研究指出个体差异、隐私风险、BCI应用场景的扩展研究等值得进一步探讨。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc3c/8591067/6afe5cfc26f1/fpsyg-12-771591-g001.jpg

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