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Noninvasive Electroencephalogram Based Control of a Robotic Arm for Writing Task Using Hybrid BCI System

机译:基于无创性脑电图的混合BCI系统用于编写任务的机械臂控制

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摘要

A novel hybrid brain-computer interface (BCI) based on the electroencephalogram (EEG) signal which consists of a motor imagery- (MI-) based online interactive brain-controlled switch, “teeth clenching” state detector, and a steady-state visual evoked potential- (SSVEP-) based BCI was proposed to provide multidimensional BCI control. MI-based BCI was used as single-pole double throw brain switch (SPDTBS). By combining the SPDTBS with 4-class SSEVP-based BCI, movement of robotic arm was controlled in three-dimensional (3D) space. In addition, muscle artifact (EMG) of “teeth clenching” condition recorded from EEG signal was detected and employed as interrupter, which can initialize the statement of SPDTBS. Real-time writing task was implemented to verify the reliability of the proposed noninvasive hybrid EEG-EMG-BCI. Eight subjects participated in this study and succeeded to manipulate a robotic arm in 3D space to write some English letters. The mean decoding accuracy of writing task was 0.93 ± 0.03. Four subjects achieved the optimal criteria of writing the word “HI” which is the minimum movement of robotic arm directions (15 steps). Other subjects had needed to take from 2 to 4 additional steps to finish the whole process. These results suggested that our proposed hybrid noninvasive EEG-EMG-BCI was robust and efficient for real-time multidimensional robotic arm control.
机译:一种基于脑电图(EEG)信号的新型混合脑机接口(BCI),包括基于运动图像(MI-)的在线交互式脑控开关,“牙齿紧握”状态检测器和稳态视觉系统提出了基于诱发电位(SSVEP)的BCI以提供多维BCI控制。基于MI的BCI用作单刀双掷大脑开关(SPDTBS)。通过将SPDTBS与基于4类SSEVP的BCI相结合,可以在三维(3D)空间中控制机械臂的运动。另外,从脑电信号记录的“牙齿紧握”状态的肌肉伪影(EMG)被检测并用作中断器,可以初始化SPDTBS的陈述。实时写作任务被实施以验证所提出的无创混合脑电图-EMG-BCI的可靠性。八名受试者参加了这项研究,并成功地在3D空间中操纵了机械臂以写一些英文字母。写作任务的平均解码精度为0.93±0.03。四名受试者达到了写出“ HI”一词的最佳标准,这是机器人手臂方向的最小移动量(15个步骤)。其他主题需要采取2到4个额外的步骤来完成整个过程。这些结果表明,我们提出的混合无创EEG-EMG-BCI对于实时多维机械臂控制是鲁棒且高效的。

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