北京生物医学工程

基于高级控制策略的脑-机接口控制机械臂系统

Brain-computer interface controlled robotic arm system based on high-level control strategy

作者：李红卫陈小刚

单位：中国人民解放军第161医院医学工程科(湖北武汉 430010)<p>中国医学科学院北京协和医学院生物医学工程研究所(天津 300192)</p><p></p>

关键词：高级控制策略；稳态视觉诱发电位；脑-机接口；机械臂

分类号：R318.04

出版年·卷·期（页码）：2019·38·1（36-41）

摘要：

目的为了增加脑-机接口控制机械臂完成诸如抓取和放置的复杂操作的能力，本文设计与实现了一套新颖的基于脑-机接口控制的机械臂系统。方法该系统主要包括计算机视觉、稳态视觉诱发电位脑-机接口和机械臂。计算机视觉用于识别工作区物体的形状和位置，低频稳态视觉诱发电位脑-机接口允许用户选择需要被操作的物体，机械臂则自主完成抓取和放置操作。为了验证机械臂系统，选取14名健康受试者，受试者均参加了离线试验，12名受试者参与在线试验。结果12名健康受试者的在线结果表明，所构建的系统能够在6.75 s内从4个可供选择的指令中输出一个命令，且获得95.24%的平均分类正确率。结论这些结果表明稳态视觉诱发电位的脑-机接口能够为机械臂提供精确、有效的高级控制。

ObjectiveTo increase the ability of brain-computer interface to control a robotic arm to complete complex operations such as pick and place. This paper is designed and realized a novel brain-computer interface (BCI) controlled robotic arm. MethodsThe proposed system included computer vision, steady-state visual evoked potential (SSVEP)-based BCI, robotic arm. The computer vision could identify and locate objects in the workspace, the low-frequency SSVEP-based BCI allowed the user to select the objects that need to be operated. The robotic arm could autonomously pick and place the selected object. In order to verify the robotic arm system, 14 healthy subjects were selected and all of them participated in the off-line test，12 subjects participated in the on-line test.Results Online results involving twelve subjects indicated that a command for the propose system could be selected from four possible choices in 6.75 s with 95.24% accuracy.Conclusion These results demonstrate an SSVEP-based BCI can provide accurate and efficient high-level control of a robotic arm.

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