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基于想象运动和视觉注意的混合脑机接口。

Toward a hybrid brain-computer interface based on imagined movement and visual attention.

机构信息

Institute for Knowledge Discovery, BCI Lab, Graz University of Technology, 8010 Graz, Austria.

出版信息

J Neural Eng. 2010 Apr;7(2):26007. doi: 10.1088/1741-2560/7/2/026007. Epub 2010 Mar 23.

Abstract

Brain-computer interface (BCI) systems do not work for all users. This article introduces a novel combination of tasks that could inspire BCI systems that are more accurate than conventional BCIs, especially for users who cannot attain accuracy adequate for effective communication. Subjects performed tasks typically used in two BCI approaches, namely event-related desynchronization (ERD) and steady state visual evoked potential (SSVEP), both individually and in a 'hybrid' condition that combines both tasks. Electroencephalographic (EEG) data were recorded across three conditions. Subjects imagined moving the left or right hand (ERD), focused on one of the two oscillating visual stimuli (SSVEP), and then simultaneously performed both tasks. Accuracy and subjective measures were assessed. Offline analyses suggested that half of the subjects did not produce brain patterns that could be accurately discriminated in response to at least one of the two tasks. If these subjects produced comparable EEG patterns when trying to use a BCI, these subjects would not be able to communicate effectively because the BCI would make too many errors. Results also showed that switching to a different task used in BCIs could improve accuracy in some of these users. Switching to a hybrid approach eliminated this problem completely, and subjects generally did not consider the hybrid condition more difficult. Results validate this hybrid approach and suggest that subjects who cannot use a BCI should consider switching to a different BCI approach, especially a hybrid BCI. Subjects proficient with both approaches might combine them to increase information throughput by improving accuracy, reducing selection time, and/or increasing the number of possible commands.

摘要

脑机接口(BCI)系统并非对所有用户都有效。本文介绍了一种新的任务组合,它可以启发更精确的 BCI 系统,尤其是对于那些无法达到有效通信所需精度的用户。受试者分别执行了两种 BCI 方法中常用的任务,即事件相关去同步(ERD)和稳态视觉诱发电位(SSVEP),以及一种将两种任务相结合的“混合”任务。记录了三个条件下的脑电图(EEG)数据。受试者想象移动左手或右手(ERD),专注于两个振荡视觉刺激之一(SSVEP),然后同时执行这两个任务。评估了准确性和主观指标。离线分析表明,一半的受试者没有产生可以准确区分至少一种任务的脑模式。如果这些受试者在尝试使用 BCI 时产生可比较的 EEG 模式,这些受试者将无法进行有效的交流,因为 BCI 会犯太多错误。结果还表明,切换到 BCI 中使用的不同任务可以提高一些用户的准确性。切换到混合方法完全消除了这个问题,而且受试者通常不认为混合条件更难。结果验证了这种混合方法,并表明无法使用 BCI 的受试者应考虑切换到不同的 BCI 方法,特别是混合 BCI。熟练掌握这两种方法的受试者可以将它们结合起来,通过提高准确性、减少选择时间和/或增加可能的命令数量来增加信息吞吐量。

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