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基于脑电图的光标控制开发中的人机并行训练。

Parallel man-machine training in development of EEG-based cursor control.

作者信息

Kostov A, Polak M

机构信息

Faculty of Rehabilitation Medicine, The University of Alberta, Edmonton, Canada.

出版信息

IEEE Trans Rehabil Eng. 2000 Jun;8(2):203-5. doi: 10.1109/86.847816.

Abstract

A new parallel man-machine training approach to brain-computer interface (BCI) succeeded through a unique application of machine learning methods. The BCI system could train users to control an animated cursor on the computer screen by voluntary electroencephalogram (EEG) modulation. Our BCI system requires only two to four electrodes, and has a relatively short training time for both the user and the machine. Moving the cursor in one dimension, our subjects were able to hit 100% of randomly selected targets, while in two dimensions, accuracies of approximately 63% and 76% was achieved with our two subjects.

摘要

一种用于脑机接口(BCI)的新型并行人机训练方法通过机器学习方法的独特应用取得了成功。该BCI系统可以训练用户通过自主脑电图(EEG)调制来控制计算机屏幕上的动画光标。我们的BCI系统仅需要两到四个电极,并且用户和机器的训练时间都相对较短。在一维移动光标时,我们的受试者能够100%击中随机选择的目标,而在二维情况下,我们的两名受试者分别实现了约63%和76%的准确率。

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