Human–computer interface (HCI) systems are extending their boundaries in our daily life and becoming an important subject in biomedical engineering. Electrooculogram (EOG) signal as an input for such systems stems from the corneoretinal standing potential, which can be used for monitoring human eye rotation. Higher amplitude, better signal-to-noise ratio, and much easier recording conditions compared with electroencephalography, make it an important input modality for HCI systems. In this article, real-time processing and cost-effective (< 100$) HCI system was designed and developed based on the EOG signals. The required electrodes were embedded in updated eyeglasses for easy electrode placement over the subject’s face. EOG signals were acquired by the subject’s eye movement toward the four middle parts of the screen edges of a laptop placed in front of them. The system training for each subject ameliorated system withstanding against the blink and wrinkle artifact. Finally, the required commands for quadcopter navigation (up, down, left, and right) generated with 0.6-s total delay and 94.8% of system accuracy in detecting the correct eye movements. A real quadcopter navigation experiment based on the standard navigation interface and the developed HCI system represented the system accuracy, robustness, and usefulness.

中文翻译：

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用于四轴飞行器导航的基于 EOG 的 HCI 系统

人机界面 (HCI) 系统正在扩展我们日常生活中的界限，并成为生物医学工程中的一个重要课题。作为此类系统输入的眼电图 (EOG) 信号源于角膜视网膜站立电位，可用于监测人眼旋转。与脑电图相比，更高的振幅、更好的信噪比和更容易的记录条件使其成为 HCI 系统的重要输入方式。在本文中，基于 EOG 信号设计和开发了实时处理和具有成本效益（< 100 美元）的 HCI 系统。所需的电极嵌入在更新的眼镜中，以便于将电极放置在受试者的脸上。EOG 信号是通过受试者的眼睛向放置在他们面前的笔记本电脑屏幕边缘的四个中间部分移动而获得的。每个科目的系统训练改善了系统抵抗眨眼和皱纹伪影的能力。最后，四轴飞行器导航（向上、向下、向左和向右）所需的命令以 0.6 秒的总延迟和 94.8% 的系统准确度生成，以检测正确的眼球运动。基于标准导航界面和开发的人机交互系统的真实四轴飞行器导航实验代表了系统的准确性、鲁棒性和实用性。8% 的系统准确度检测正确的眼球运动。基于标准导航界面和开发的人机交互系统的真实四轴飞行器导航实验代表了系统的准确性、鲁棒性和实用性。8% 的系统准确度检测正确的眼球运动。基于标准导航界面和开发的人机交互系统的真实四轴飞行器导航实验代表了系统的准确性、鲁棒性和实用性。