增强现实场景下基于稳态视觉诱发电位的机械臂控制系统  

Control System of Robotic Arm Based on Steady-State Visual Evoked Potentials in Augmented Reality Scenarios

作　　者：陈玲玲 陈鹏飞[1,2,4] 谢良 许敏鹏[4,5] 徐登科 闫慧炯 罗治国[3,4] 闫野[3,4] 印二威 CHEN Lingling;CHEN Pengfei;XIE Liang;XU Minpeng;XU Dengke;YAN Huijiong;LUO Zhiguo;YAN Ye;YIN Erwei(School of Artificial Intelligence and Data Science,Hebei University of Technology,Tianjin 300130,China;Engineering Research Center of Intelligent Rehabilitation and Detecting Technology,Ministry of Education,Tianjin 300130,China;National Innovation Institute of Defense Technology,Academy of Military Sciences China,Beijing 100071,China;Tianjin Artificial Intelligence Innovation Center,Tianjin 300450,China;Tianjin University,Tianjin 300072,China;Institute of Communication and Signaling,Chinese Academy of Railway Sciences,Beijing 100081,China)

机构地区：[1]河北工业大学人工智能与数据科学学院,天津300130 [2]智能康复装置与检测技术教育部工程研究中心,天津300130 [3]军事科学院国防科技创新研究院,北京100071 [4]天津(滨海)人工智能创新中心,天津300450 [5]天津大学,天津300072 [6]中国铁道科学研究院通信信号研究所,北京100081

出　　处：《电子与信息学报》2022年第2期496-506,共11页Journal of Electronics & Information Technology

基　　金：国家自然科学基金(61901505,61703407,62076250);河北省自然科学基金(F2021202021);国家创新平台开放基金(2019YJ192)。

摘　　要：目前脑控机械臂在医疗康复等多个领域展现出了宽广的应用前景,但也存在灵活性较差、使用者易疲劳等不足之处。针对上述不足,该文设计一套增强现实(AR)环境下基于稳态视觉诱发电位(SSVEP)的机械臂异步控制系统。利用滤波器组典型相关分析方法(FBCCA)实现对12个目标的识别;提出基于投票策略和差值预测的动态窗口,实现刺激时长的自适应调节;利用伪密钥实现机械臂异步控制,完成拼图任务。试验结果表明,动态窗口可以根据受试者状态自动调整刺激时长,离线平均准确度为(93.11±5.85)%,平均信息传输速率(ITR)为(59.69±8.11)bit·min^(–1)。在线单次命令平均选择时间为2.18 s,有效地减轻受试者的视觉疲劳。每位受试者均能迅速完成拼图任务,证明了该人机交互方法的可行性。At present,brain-controlled robotic arms have shown broad application prospects in many fields such as medical rehabilitation,but they also have disadvantages such as poor flexibility and fatigue of users.In view of the above shortcomings,an asynchronous control system based on Steady-State Visual Evoked Potential(SSVEP)in an Augmented Reality(AR)environment is designed.A Filter Bank Canonical Correlation Analysis(FBCCA)is applied to identify 12 targets.A dynamic window based on voting strategy and difference prediction is proposed to adjust the stimulus duration adaptively.The robotic arm is asynchronously controlled by pseudo-key to complete the task of the Jigsaw Puzzle.The experimental results demonstrate that the dynamic window can automatically adjust the length of stimulation according to the state of subjects.The average offline accuracy is(93.11±5.85)%,the average offline ITR is(59.69±8.11)bit·min^(–1).The average selection time of an online single command is 2.18 s.It can reduce the visual fatigue of the subjects effectively.Each subject can accomplish the puzzle task quickly,which indicates the feasibility of this human-computer interaction method.

关 键 词：脑机接口 机械臂 增强现实 动态窗口 异步控制 

分 类 号：TP242.6[自动化与计算机技术—检测技术与自动化装置] R318[自动化与计算机技术—控制科学与工程]