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EEG- and EOG-Based Asynchronous Hybrid BCI: A System Integrating a Speller, a Web Browser, an E-Mail Client, and a File Explorer
IEEE Transactions on Neural Systems and Rehabilitation Engineering ( IF 4.8 ) Pub Date : 2019-12-20 , DOI: 10.1109/tnsre.2019.2961309
Shenghong He , Yajun Zhou , Tianyou Yu , Rui Zhang , Qiyun Huang , Lin Chuai , Madah-Ul- Mustafa , Zhenghui Gu , Zhu Liang Yu , Huiling Tan , Yuanqing Li

This paper presents a new asynchronous hybrid brain-computer interface (BCI) system that integrates a speller, a web browser, an e-mail client, and a file explorer using electroencephalographic (EEG) and electrooculography (EOG) signals. More specifically, an EOG-based button selection method, which requires the user to blink his/her eyes synchronously with the target button’s flashes during button selection, is first presented. Next, we propose a mouse control method by combining EEG and EOG signals, in which the left-/right-hand motor imagery (MI)-related EEG is used to control the horizontal movement of the mouse and the blink-related EOG is used to control the vertical movement of the mouse and to select/reject a target. These two methods are further combined to develop the integrated hybrid BCI system. With the hybrid BCI, users can input text, access the internet, communicate with others via e-mail, and manage files in their computer using only EEG and EOG without any body movements. Ten healthy subjects participated in a comprehensive online experiment, and superior performance was achieved compared with our previously developed P300- and MI-based BCI and some other asynchronous BCIs, therefore demonstrating the system’s effectiveness.

中文翻译:


基于 EEG 和 EOG 的异步混合 BCI:集成拼写器、Web 浏览器、电子邮件客户端和文件资源管理器的系统



本文提出了一种新型异步混合脑机接口(BCI)系统,该系统使用脑电图(EEG)和眼电图(EOG)信号集成了拼写器、网络浏览器、电子邮件客户端和文件浏览器。更具体地,首先提出了一种基于EOG的按钮选择方法,该方法要求用户在选择按钮时与目标按钮的闪烁同步地眨眼。接下来,我们提出了一种结合脑电图和眼电图信号的鼠标控制方法,其中左/右手运动想象(MI)相关的脑电图用于控制鼠标的水平移动,并且使用眨眼相关的眼电图控制鼠标的垂直移动并选择/拒绝目标。这两种方法进一步结合起来开发集成的混合BCI系统。借助混合脑机接口,用户只需使用脑电图和眼电图即可输入文本、访问互联网、通过电子邮件与他人交流以及管理计算机中的文件,而无需任何身体动作。十名健康受试者参与了全面的在线实验,与我们之前开发的基于 P300 和 MI 的 BCI 以及其他一些异步 BCI 相比,取得了优异的性能,从而证明了系统的有效性。
更新日期:2020-03-04
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