The BCI competition III:: Validating alternative approaches to actual BCI problems
The BCI competition III:: Validating alternative approaches to actual BCI problems
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DOI：
10.1109/tnsre.2006.875642
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发表时间：
2006-06-01
影响因子：
4.9
通讯作者：
Birbaumer, Niels
中科院分区：
文献类型：
--
作者：
Blankertz, Benjamin;Mueller, Klaus-Robert;Birbaumer, Niels
脑机接口(BCI)是一种允许用户控制具有大脑活动的外部设备的系统。尽管概念验证早在几十年前就已经给出，但将用户意图可靠地转换为设备控制命令仍然是一个重大挑战。成功需要两个自适应控制器的有效交互：用户的大脑产生编码意图的大脑活动，以及将该活动转换为设备控制命令的BCI系统。为了促进这种相互作用，许多实验室正在探索各种信号分析技术，以提高脑机接口系统对用户的适应性。在文献中，许多机器学习和模式分类算法在离线分析中应用于BCI数据时都取得了令人印象深刻的结果。然而，更难评估它们在实际在线使用中的相对价值。已经组织了BCI数据竞赛，以提供对替代方法的客观正式评估。由于人们对前两届BCI竞赛的浓厚兴趣，我们组织了第三届BCI竞赛，以解决BCI研究中几个最困难和最重要的分析问题。该文件描述了提供给竞争对手的数据集，并概述了结果。
A brain-computer interface (BCI) is a system that allows its users to control external devices with brain activity. Although the proof-of-concept was given decades ago, the reliable translation of user intent into device control commands is still a major challenge. Success requires the effective interaction of two adaptive controllers: the user's brain, which produces brain activity that encodes intent, and the BCI system, which translates that activity into device control commands. In order to facilitate this interaction, many laboratories are exploring a variety of signal analysis techniques to improve the adaptation of the BCI system to the user. In the literature, many machine learning and pattern classification algorithms have been reported to give impressive results when applied to BCI data in offline analyses. However, it is more difficult to evaluate their relative value for actual online use. BCI data competitions have been organized to provide objective formal evaluations of alternative methods. Prompted by the great interest in the first two BCI Competitions, we organized the third BCI Competition to address several of the most difficult and important analysis problems in BCI research. The paper describes the data sets that were provided to the competitors and gives an overview of the results.