摘要
脑机交互(BCI)是一种变革性的人机交互,旨在绕过外周神经和肌肉系统直接把脑神经的感知觉、表象或思维活动转化为动作,以进一步改善或提高人类的生活质量。脑磁图(MEG)测量神经元电活动产生的磁场,具有非接触式测量、时空分辨率高和准备方便等独特优势,是一种新的BCI驱动信号,基于脑磁图的脑机交互(MEG-BCI)研究具有重要脑科学意义和潜在应用价值。迄今为止,少有文献阐述MEG-BCI涉及的关键技术问题,为此本文聚焦MEG-BCI关键技术,详述了实用MEG-BCI系统中涉及的信号采集技术、MEG-BCI实验范式设计、MEG信号分析和解码关键技术、MEG-BCI神经反馈技术及其智能化方法。最后,本文还讨论了MEGBCI存在的问题和未来发展趋势,期望本文为MEG-BCI创新研究提供更多有益思路。
Brain-computer interaction(BCI)is a transformative human-computer interaction,which aims to bypass the peripheral nerve and muscle system and directly convert the perception,imagery or thinking activities of cranial nerves into actions for further improving the quality of human life.Magnetoencephalogram(MEG)measures the magnetic field generated by the electrical activity of neurons.It has the unique advantages of non-contact measurement,high temporal and spatial resolution,and convenient preparation.It is a new BCI driving signal.MEG-BCI research has important brain science significance and potential application value.So far,few documents have elaborated the key technical issues involved in MEG-BCI.Therefore,this paper focuses on the key technologies of MEG-BCI,and details the signal acquisition technology involved in the practical MEG-BCI system,the design of the MEG-BCI experimental paradigm,the MEG signal analysis and decoding key technology,MEG-BCI neurofeedback technology and its intelligent method.Finally,this paper also discusses the existing problems and future development trends of MEG-BCI.It is hoped that this paper will provide more useful ideas for MEG-BCI innovation research.
作者
徐浩天
龚安民
丁鹏
罗建功
陈超(综述)
伏云发(审校)
XU Haotian;GONG Anmin;DING Peng;LUO Jiangong;CHEN Chao;FU Yunfa(Faculty of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500,P.R.China;Brain Cognition and Brain-computer Intelligence Integration Group,Kunming University of Science and Technology,Kunming 650500,P.R.China;School of Information Engineering,Chinese People’s Armed Police Force Engineering University,Xi'an 710000,P.R.China;Tianjin University of Technology School of Electrical and Electronic Engineering,Tianjin 300000,P.R.China)
出处
《生物医学工程学杂志》
EI
CAS
CSCD
北大核心
2022年第1期198-206,共9页
Journal of Biomedical Engineering
基金
国家自然科学基金资助项目(81771926,61763022,82172058,62006246)。
关键词
脑磁图
脑机交互
智能脑机交互
基于脑磁图的脑机交互实验范式设计
脑磁图特征提取
Magnetoencephalography
Brain-computer interface
Intelligent brain-computer interface
Magnetoencephalography-brain-computer interface experimental paradigm design
Magnetoencephalography feature extraction
