Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, People's Republic of China.
J Neural Eng. 2010 Jun;7(3):036003. doi: 10.1088/1741-2560/7/3/036003. Epub 2010 Apr 19.
Not until recently have motion-onset visual evoked potentials (mVEPs) been explored as a modality for brain-computer interface (BCI) applications. In this study, the first online BCI system based on mVEPs is presented, in which selection is discerned by subjects' focused attention to the moving cursor at a target virtual button. An adaptive approach was used to adjust the number of trial presentations according to the participants' online performance. With the EEG signal acquired from only a single channel, an acceptable information transfer rate of 42.1 bits min(-1) was achieved, averaged by 12 subjects. Furthermore, an online application for the Google search system was developed based on this paradigm. The promising results, that all of 12 participants were able to operate the system freely, validate the feasibility of a practical motion-onset VEP-based BCI which could be embedded into computer screen elements, such as menu, button and icon, for various applications.
直到最近，运动起始视觉诱发电位（mVEPs）才被探索作为脑机接口（BCI）应用的一种模态。在这项研究中，我们提出了第一个基于 mVEPs 的在线 BCI 系统，其中通过被试者将注意力集中在目标虚拟按钮上的移动光标来进行选择。我们使用自适应方法根据参与者的在线表现来调整试验呈现的次数。仅使用单个通道获取的 EEG 信号，通过 12 名受试者的平均计算，获得了可接受的 42.1 位/分钟的信息传输率。此外，还基于该范式开发了一个适用于 Google 搜索系统的在线应用程序。所有 12 名参与者都能够自由操作该系统，这一令人鼓舞的结果验证了基于运动起始 VEP 的实用 BCI 的可行性，这种 BCI 可以嵌入到计算机屏幕元素中，如菜单、按钮和图标，适用于各种应用。
