School of Automation Science and Engineering, South China University of Technology, Guangzhou 510640, China.
Comput Math Methods Med. 2013;2013:750934. doi: 10.1155/2013/750934. Epub 2013 Apr 18.
Brain-computer interface-based communication plays an important role in brain-computer interface (BCI) applications; electronic mail is one of the most common communication tools. In this study, we propose a hybrid BCI-based mail client that implements electronic mail communication by means of real-time classification of multimodal features extracted from scalp electroencephalography (EEG). With this BCI mail client, users can receive, read, write, and attach files to their mail. Using a BCI mouse that utilizes hybrid brain signals, that is, motor imagery and P300 potential, the user can select and activate the function keys and links on the mail client graphical user interface (GUI). An adaptive P300 speller is employed for text input. The system has been tested with 6 subjects, and the experimental results validate the efficacy of the proposed method.
基于脑-机接口的通信在脑-机接口（BCI）应用中起着重要作用；电子邮件是最常见的通信工具之一。在这项研究中，我们提出了一种基于混合 BCI 的邮件客户端，通过实时分类从头皮脑电图（EEG）中提取的多模态特征来实现电子邮件通信。使用这种基于 BCI 的邮件客户端，用户可以接收、阅读、编写和附加文件到他们的邮件中。用户可以使用混合脑信号（即运动想象和 P300 电位）的 BCI 鼠标来选择和激活邮件客户端图形用户界面（GUI）上的功能键和链接。自适应 P300 拼写器用于文本输入。该系统已经在 6 名受试者中进行了测试，实验结果验证了该方法的有效性。
