脑机接口:从神奇到现实转变
电子科技大学生命科学与技术学院神经信息教育部重点实验室,成都 610054
Brain Computer Interface: Translation from Miracle to Reality
Key Laboratory for Nearo Information of Ministry of Education School of Life Science and Technology,
University of Electronic Science and Technology of China, Chengdu 610054, China
摘要 脑机接口技术(BCI)是指基于在线脑信号的脑与外环境之间的交互技术。本文介绍了BCI涉及的几个主要方面,并展望了BCI技术的未来发展
关键词 :
脑-机接口 ,
未来展望
Abstract :Braincomputer interface (BCI) is the technique which uses online brainsignal processing to enhance the interactions between human and environments. This article summarizes the main aspects of BCI, and the challenges for BCI from miracle to reality
Key words :
brain computer interface
challenges for future
基金资助: 国家自然科学基金(81330032)
[1]刘铁军,张锐,徐鹏.基于运动想象的脑机接口关键技术研究[J]. 中国生物医学工程学报,2014, 33(6):644-651.
[2]刘伟杰, 段炼, 戴瑞娜, 等.高生态效度的双脑神经反馈平台 [J]. 中国生物医学工程学报,2014, 33(6): 652-658.
[3]曹艳, 郑筱祥. 植入式脑机接口发展概况 [J] .中国生物医学工程学报,2014, 33(6): 659-665.
[4]吴俊, 杨雅, 俞祝良, 等.基于马尔科夫切换过程的运动想象信号分类方法.中国生物医学工程学报,2014, 33(6): 666-672.
[5]尧德中,刘铁军,雷旭,等.基于脑电的脑-机接口:关键技术和应用前景 [J].电子科技大学学报, 2009, 3(5): 550-554.
[6]Gao Shangkai, Wang Yijun, Gao Xiaorong, et al. Visual and auditory braincomputer interfaces [J]. IEEE Trans on Biomed Eng, 2014, 61(5): 1436- 1447.
[7]高上凯. 浅谈脑一机接口的发展现状与挑战 [J]. 中国生物医学工程学报,2007, 26(6): 801-809.
[8]Xu Minpeng, Chen Long, Zhang Lixin, et al.A visual parallelBCI speller based on the timefrequency coding strategy [J]. J Neural Eng, 2014, 11(2):026014.
[9]Yin Eewei, Zhou Zongtan, Jiang Jun, et al. A novel hybrid BCI speller based on the incorporation of SSVEP into the P300 paradigm [J]. J Neural Eng, 2013, 10(2):026012[10]Xie Jun, Xu Guanghua, Wang Jiang, et al. Addition of visual noise boosts evoked potentialbased braincomputer interface [J].Sci Rep, 2014, 14(4):4953.
[11]Liu Ye, Li Mingfen, Zhang Hao, et al.A tensorbased scheme for stroke patients' motor imagery EEG analysis in BCIFES rehabilitation training [J]. J Neurosci Methods, 2014,222:238-249.
[12]王行愚,金晶,张宇,等.脑控:基于脑-机接口的人机融合控制 [J].自动化学报, 2013,39(3):208-223.
[13]Cao L, Li J, Ji H, et al. A hybrid brain computer interface system based on the neurophysiological protocol and brainactuated switch for wheelchair control [J]. J Neurosci Methods,2014, 229:33-43.
[14]Wang H, Xu Dong. Comprehensive common spatial patterns with temporal structure information of EEG data: minimizing nontask related EEG component [J]. IEEE Trans Biomed Eng, 2012, 59(9):2496-2505.
[15]Wei Pengfei, He Wei, Zhou Yi, et al. Performance of motor imagery braincomputer interface based on anodal transcranial direct current stimulation modulation [J]. IEEE Trans Neural Syst Rehabil Eng, 2013,21(3):404-415.
[16]Xu Peng, Tian Chunyang, ZhangYangsong, et al. Cortical network properties revealed by SSVEP in anesthetized rats [J]. Sci Rep, 2013, 3: 2496.
[17]尧德中, 吴丹, 赖永秀, 等. 基于脑电和磁共振的音乐脑机制研究 [J]. 中国生物医学工程学报, 2014,33(6): 673-676.
[18]Xu Lei, Yang Ping, Yao Dezhong. An empirical bayesianframework for brain computer interfaces [J]. IEEE Trans Neural Syst Rehabil Eng, 2009, 17(6): 521-529.