引用本文:刘迎欣,李明,于扬,曾令李,周宗潭,胡德文.混合脑机接口在人机交互领域的应用综述[J].控制理论与应用,2023,40(12):2077~2089.[点击复制]
Liu Ying-xin,LI Ming,YU Yang,ZENG Ling-li,ZHOU Zong-tan,HU De-wen.Review of hybrid brain-computer interface applications in human-computer interaction[J].Control Theory and Technology,2023,40(12):2077~2089.[点击复制]
混合脑机接口在人机交互领域的应用综述
Review of hybrid brain-computer interface applications in human-computer interaction
摘要点击 1675  全文点击 473  投稿时间:2023-04-19  修订日期:2023-10-09
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DOI编号  10.7641/CTA.2023.30237
  2023,40(12):2077-2089
中文关键词  脑机接口  人机交互  混合脑机接口  多模态
英文关键词  brain computer interface  human computer interaction  hybrid brain computer interface  multimodal
基金项目  科技创新2030项目(2022ZD0208903), 国家自然科学基金项目(62006239, 61722313, 62036013), 霍英东教育基金项目(161057)资助.
作者单位E-mail
刘迎欣 国防科技大学 2209449676@qq.com 
李明 国防科技大学  
于扬* 国防科技大学 yuyangnudt@hotmail.com 
曾令李 国防科技大学  
周宗潭 国防科技大学  
胡德文 国防科技大学  
中文摘要
      在人机交互系统中, 如何使计算机更好地理解人类意图? 随着智能科技的发展, 这个问题越来越受到人们 的关注. 脑机接口技术与脑科学密切结合, 在人机交互领域具有独特的应用优势. 混合脑机接口通过信息融合实现 多种模态的互补共促, 成为人机交互领域未来发展的新方向和新趋势. 本文首先介绍了混合脑机接口的类型和技 术原理, 并着重探讨了其关键技术“信号融合方式”; 随后, 从“ 控制者”和“监测者”的角度出发, 对混合脑机接口在人 机交互领域的研究现状进行了统计分析, 结果显示, 混合脑机接口更多以“监控者”的角色应用于人机交互系统, 其 中情感识别、认知状态评估等均是关注度较高的应用方向; 最后, 对混合脑机接口在人机交互中的应用前景进行了 展望.
英文摘要
      How to enhance computers’ understanding of human intentions in human-computer interaction systems has attracted increasing attention with the development of intelligent technology. The integration of brain-computer interface technology with neuroscience offers unique advantages in the field of human-computer interaction. Hybrid brain-computer interfaces, through information fusion, enable the complementary integration of multiple modalities, paving the way for future advancements in human-computer interaction. This paper first introduces the types and technical principles of hybrid brain-computer interfaces, with a particular emphasis on the key technology of “signal fusion”. Subsequently, from the perspectives of “controllers” and “monitors”, a statistical analysis of the current research status of hybrid braincomputer interfaces in human-computer interaction is conducted. The results reveal that hybrid brain-computer interfaces are primarily applied as “monitors” in human-computer interaction systems, with a high focus on applications such as emotion recognition and cognitive state assessment. Finally, an outlook on the application prospects of hybrid braincomputer interfaces in human-computer interaction is provided.