首页> 外文期刊>Neural Systems and Rehabilitation Engineering, IEEE Transactions on >Electroencephalography (EEG)-Based Brain–Computer Interface (BCI): A 2-D Virtual Wheelchair Control Based on Event-Related Desynchronization/Synchronization and State Control
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Electroencephalography (EEG)-Based Brain–Computer Interface (BCI): A 2-D Virtual Wheelchair Control Based on Event-Related Desynchronization/Synchronization and State Control

机译:基于脑电图(EEG)的脑机接口(BCI):基于事件相关的去同步/同步和状态控制的二维虚拟轮椅控制

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This study aims to propose an effective and practical paradigm for a brain–computer interface (BCI)-based 2-D virtual wheelchair control. The paradigm was based on the multi-class discrimination of spatiotemporally distinguishable phenomenon of event-related desynchronization/synchronization (ERD/ERS) in electroencephalogram signals associated with motor execution/imagery of right/left hand movement. Comparing with traditional method using ERD only, where bilateral ERDs appear during left/right hand mental tasks, the 2-D control exhibited high accuracy within a short time, as incorporating ERS into the paradigm hypothetically enhanced the spatiotemoral feature contrast of ERS versus ERD. We also expected users to experience ease of control by including a noncontrol state. In this study, the control command was sent discretely whereas the virtual wheelchair was moving continuously. We tested five healthy subjects in a single visit with two sessions, i.e., motor execution and motor imagery. Each session included a 20 min calibration and two sets of games that were less than 30 min. Average target hit rate was as high as 98.4% with motor imagery. Every subject achieved 100% hit rate in the second set of wheelchair control games. The average time to hit a target 10 m away was about 59 s, with 39 s for the best set. The superior control performance in subjects without intensive BCI training suggested a practical wheelchair control paradigm for BCI users.
机译:这项研究旨在为基于脑机接口(BCI)的二维虚拟轮椅控制提出一种有效而实用的范例。该范例基于与运动执行/左右手运动图像相关的脑电图信号中事件相关失步/同步(ERD / ERS)的时空可区分现象的多类判别。与仅使用ERD的传统方法(在左/右手的脑部任务中出现双侧ERD)相比,二维控制在短时间内显示出较高的准确性,因为将ERS纳入范例中可以提高ERS与ERD的时空特征对比。我们还希望用户通过包含非控制状态来体验易于控制。在这项研究中,控制命令是离散发送的,而虚拟轮椅则是连续移动的。我们通过两次访问(即运动执行和运动图像)在一次访问中测试了五名健康受试者。每节课包括20分钟的校准和少于30分钟的两组游戏。运动图像的平均目标命中率高达98.4%。在第二套轮椅控制游戏中,每个受试者的命中率均达到100%。击中目标10 m的平均时间约为59 s,最佳设置为39 s。在未经BCI强化训练的受试者中,出色的控制性能为BCI用户提供了一种实用的轮椅控制范例。

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