Investigating natural control signals for brain-computer interfaces /
Investigating natural control signals for brain-computer interfaces /
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研究脑机接口的自然控制信号 /
DOI：
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发表时间：
2013
期刊：
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通讯作者：
A. S. Koerner
中科院分区：
文献类型：
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作者：
A. S. Koerner
基于脑电的脑机接口(BCI)允许用户通过从大脑皮层读取的信号直接与外部世界交流。这些系统通常需要用户培训才能生成适合使用的信号。然而，用户控制这种系统的能力是可变的，所涉及的变量还没有完全理解。在这项工作中，我们为识别和使用与反馈相关的EEG信号奠定了基础，既可以增强现有的运动图像BCI，也可以提供一种新的控制机制。我们进行了一个模拟的在线实验，指示用户在一个维度上将光标从屏幕中心移向位于左侧或右侧两端的目标。在第二章中，我们将演示视觉反馈的局部方面(在单个光标移动尺度上)如何增强现有系统或为新系统提供控制信号。在第三章中，我们展示了视觉反馈的全局方面如何影响运动想象的表现。反馈价不像最初认为的那样为运动想象分类提供更稳定的信号，相反，反馈价似乎旋转了运动想象特征空间。在第四章中，我们将在在线实时环境中验证第二章中的发现。此外，我们还展示了利用用户满意和不满意的局部方面作为主要控制信号的BCI系统的实用性。事实证明，这是一个有用的、稳定的系统，它提供了对传统运动想象范式的改进
EEG-based brain computer interfaces (BCI) allow users to communicate with the outside world directly through signals read from the cortex. These systems typically require user training to generate signals appropriate for use. However, user ability to control such a system is variable and the variables involved are not fully understood. In this work, we present the foundation for the identification and use of feedback-related EEG signals to both augment existing motor imagery BCIs as well as to provide a novel mechanism for control. We conducted a simulated online experiment where users were instructed to move a cursor in one dimension from the center of the screen towards a target located at the left or right extremes. In Chapter 2 we demonstrate how local aspects of visual feedback (on a single cursor movement scale) can augment existing systems or provide control signals for novel ones. In Chapter 3, we demonstrate how global aspects of visual feedback can affect motor imagery performance. Rather than more positive feedback valence providing a more stable signal for motor imagery classification (as originally thought), feedback valence instead appears to rotate the motor imagery feature space. In Chapter 4 we validate our findings from Chapter 2 in an online, real-time setting. In addition, we demonstrate the utility of a BCI system that utilizes local aspects of user satisfaction and dissatisfaction as a principal control signal. This proves to be a useful, stable system that provides improvement over a traditional motor imagery paradigm