Balancing an Inverted Pendulum with an EEG-Based BCI

Jingsheng Tang, E. Yin, Jun Jiang, Zongtan Zhou, D. Hu
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引用次数: 1

Abstract

To research the brain computer interface (BCI) for dynamic objects control, in this study, we constructed a BCI paradigm for balancing a virtual inverted pendulum on a cart (IPC). In the paradigm, subjects balanced the pendulum by imaging left/right movements. Not only was the direction, but also the strength of motor imagery was estimated simultaneously from the EEG signals, to generate suitable control force for IPC. Additionally, to solve the inconsistent problem between offline training and online controlling, a special online training experiment was designed to obtain more robust parameters of BCI. Three graduate subjects participated in this study, and two of them fast grasped the skill of IPC balancing, achieved balancing time of about 20 seconds. The results showed that the paradigm in this study was feasible and efficient for dynamic objects control.
用脑电图脑机接口平衡倒立摆
为了研究动态对象控制的脑机接口(BCI),我们构建了一个虚拟倒立摆小车(IPC)平衡的脑机接口范式。在范式中,受试者通过想象左右运动来平衡钟摆。同时从脑电信号中估计运动图像的方向和强度,为IPC产生合适的控制力。此外,为了解决离线训练与在线控制不一致的问题,设计了专门的在线训练实验,以获得更鲁棒的BCI参数。3名研究生参与了本次研究,其中2名研究生快速掌握了IPC平衡技能,达到了20秒左右的平衡时间。实验结果表明,该方法对动态目标控制是可行的、有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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