先进脑机接口理论与脑控康复车实现技术研究

项目名称： 先进脑机接口理论与脑控康复车实现技术研究

项目编号： No.91320202

项目类型： 重大研究计划

立项/批准年度： 2014

项目学科： 自动化技术、计算机技术

项目作者： 周宗潭

作者单位： 中国人民解放军国防科学技术大学

项目金额： 250万元

中文摘要： 以提高脑机接口(BCI)系统的可用性和实用性为总体目标，研究新型EEG采集技术与非晶丝MEG检测技术相结合的混合BCI大脑信息非屏蔽/非接触可靠测量与信号融合技术；以装备上述脑信号监测系统的自主康复车为基本平台，设计和开展科学实验，探索人机结合中的共享自主性问题和自适应控制主体切换方法；通过对人机反馈通道的非对称特点进行分析和设计，研究康复车的优化脑机控制策略；研究原子运动产生、转化、衔接和同步等过程的内在规律和相应的在线识别算法，构建能符合人体运动神经机理的高效康复车导航与简单目标操作和抓取控制系统。在上述人机协调控制理论探索的基础上，设计人机协调的控制机理并以此为指导设计合理的BCI范式，实现具有大脑直接通讯与控制能力的康复车高效导航和操控方法，并构建康复车原型系统验证上述脑信号采集、人机系统理论探索和实验范式设计工作，使康复车达到“即插即用、即时可用、稳定可靠、长期工作”的实用化标准

中文关键词： 脑机接口；多模态融合；脑机协同操控；脑控康复车；GMI脑磁检测技术

英文摘要： In order to improve the feasibility and practically of brain-computer interface (BCI) system, this project researches its advanced theories, technologies and application on brain-actuated rehabilitation vehicle. Firstly, efficient brain signal acquisition technologies are developed by improving and combining the EEG acquisition device and GMI sensors-based MEG acquisition device. Secondly, the data of brain activities is collected in the experiment of brain-actuated rehabilitation vehicle, and then used to develop the classification algorithms based on the brain network analysis, so that different brain activities can be probed and predicted accurately. The neural basis of the submovements (including how they are generated, cohered or synchronized) in the human motor system is investigated to improve the reliability of the classification and achieve effective brain-computer controller corresponding to the neural mechanisms of human motor system. Then, the issues about optimized BCI control strategy based on man-machine interaction theory (such as shared-control frame, decision rules and the asymmetry problem) are studied, and finally, a brain-actuated rehabilitation vehicle system is established to test and verify the advanced BCI technique. These studies could probably be meaningful in the realization of the in

英文关键词： Brain-computer interface (BCI)；Multimodal fusion；Brain-computer coordinated operation；Brain-actuated rehabilitation vehicle；GMI-based MEG