A brain-actuated wheelchair:: Asynchronous and non-invasive Brain-computer interfaces for continuous control of robots
A brain-actuated wheelchair:: Asynchronous and non-invasive Brain-computer interfaces for continuous control of robots
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DOI：
10.1016/j.clinph.2008.06.001
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发表时间：
2008-09-01
影响因子：
4.7
通讯作者：
Millan, J. del R.
中科院分区：
文献类型：
--
作者：
Galan, F.;Nuttin, M.;Millan, J. del R.
目的：评估一种异步和非侵入性的基于EEG的脑机接口（BCI）用于轮椅的连续精神控制的可行性和鲁棒性。在实验1中，两名受试者被要求在精神上驾驶真实的和模拟的轮椅从起点到目标沿着一个预先设定的路线。在这里，我们只报告了模拟轮椅的实验，我们在复杂的环境中有大量的数据，可以进行声音分析。每个受试者参加了5个实验阶段，每个阶段包括10次试验。两个连续实验阶段之间的时间是可变的（从1小时到2个月），以评估系统随时间的稳健性。预先指定的路径被分成七段，以评估系统在不同情况下的鲁棒性。为了进一步评估脑驱动轮椅的性能，受试者1参加了第二个实验，其中包括10次试验，他被要求驾驶模拟轮椅沿着10条以前从未尝试过的不同复杂和随机路径行驶。在实验1中，两个受试者能够达到100%（受试1）和80%（受试2）的最终目标沿着预先指定的轨迹在他们的最佳会话。随着时间和路径延伸获得不同的性能，这表明性能是时间和上下文相关的。在实验2中，受试者1能够达到最终目标的80%的trials.Conclusions：结果表明，受试者可以快速掌握我们的异步基于EEG的BCI控制轮椅。还有...他们要求在长时间段内自主地操作BCI，而不需要由人类操作员外部调整的自适应算法来最小化EEG非平稳性的影响。这是可能的，因为有两个关键组成部分：第一，包括一个共享的控制系统之间的BCI系统和智能模拟轮椅;第二，选择稳定的用户特定的EEG功能，最大限度地提高分离之间的精神tasks.Significance：这些结果表明，连续控制复杂的机器人设备使用所有异步和非侵入性BCI的可行性。(C)2008年国际临床神经生理学联合会。由Elsevier爱尔兰有限公司出版。保留所有权利。
Objective: To assess the feasibility and robustness of an asynchronous and non-invasive EEG-based Brain-Computer Interface (BCI) for continuous mental control of a wheelchair.Methods: In experiment 1 two Subjects were asked to mentally drive both a real and a simulated wheelchair from a starting point to a goal along a pre-specified path. Here we only report experiments with the simulated wheelchair for which we have extensive data in a complex environment that allows a sound analysis. Each subject participated in five experimental sessions, each consisting of 10 trials. The time elapsed between two consecutive experimental sessions was variable (from 1 h to 2 months) to assess the system robustness over time. The pre-specified path was divided into seven stretches to assess the system robustness in different contexts. To further assess the performance of the brain-actuated wheelchair, subject 1 participated in a second experiment consisting of 10 trials where he was asked to drive the simulated wheelchair following 10 different complex and random paths never tried before.Results: In experiment 1 the two subjects were able to reach 100% (subject 1) and 80% (subject 2) of the final goals along the pre-specified trajectory in their best sessions. Different performances were obtained over time and path stretches, what indicates that performance is time and context dependent. In experiment 2, subject 1 was able to reach the final goal in 80% of the trials.Conclusions: The results show that subjects can rapidly master our asynchronous EEG-based BCI to control a wheelchair. Also.. they call autonomously operate the BCI over long periods of time without the need for adaptive algorithms externally tuned by a human operator to minimize the impact of EEG non-stationarities. This is possible because of two key components: first, the inclusion of a shared control system between the BCI system and the intelligent simulated wheelchair; second, the selection of stable user-specific EEG features that maximize the separability between the mental tasks.Significance: These results show the feasibility of continuously controlling complex robotics devices using all asynchronous and non-invasive BCI. (C) 2008 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.