北京生物医学工程

群脑协作的协同式脑-机接口研究进展

Research progress of collaborative brain-computer interface for group brain collaboration

作者：张力新陈小翠顾斌陈龙李岑博明东

单位：天津大学精密仪器与光电子工程学院（天津 300072）；天津大学医学工程与转化医学研究院（天津 300072）

分类号：R318.04

出版年·卷·期（页码）：2020·39·5（535-541）

摘要：

传统的非侵入型脑-机接口（brain-computer interface，BCI）系统通常采用单人-单机架构，其信息传输速率较低且鲁棒性差，难以满足高精度、多指令、短时限等复杂作业的性能需求。随着传感和信息技术的迅速发展，面向多人-多机的协同式脑-机接口系统（collaborative BCI, cBCI）应运而生。cBCI可充分发挥群体智慧优势，深入挖掘群体神经响应信息，从而更高效地完成人-机交互作业。本文综述了cBCI的基本系统架构，并结合现有研究分析其在决策与控制两个应用场景下的作业特点，讨论了面向不同作业需求和系统架构的群体神经信息融合算法的优势与不足，展望了cBCI的系统优化方向与应用研究的发展趋势。

Traditional noninvasive brain-computer interface system usually adopt single-user and single-machine architecture. It’s difficult to meet the requirements of high accuracy, multiple instruction and short time delay, because of the low information transmission rate and poor robustness. With the development of sensing and information technology, the collaborative brain-computer interface based on multi-users and multi-machines has emerged. In order to complete the human- machine interaction work more efficiently, cBCI could give full play to the collective intelligence and deep digging in neural response information of group. This paper reviewed the basic architecture of the cBCI system and its application to decision-making and control. It also discussed the advantages and disadvantages of fusion algorithm for group neural response information. The system optimization direction and research trend of cBCI were proposed in the end.

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