Liu Jiarong, Wang Linyao, Wu Yingnian, He Qing
School of Instrument Science and Opto Electronics Engineering, Beijing Information Science & Technology University, Beijing 100192, P. R. China.
School of Literature and Journalism, Hubei Engineering University, Xiaogan, Hubei 432000, P. R. China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2022 Aug 25;39(4):833-840. doi: 10.7507/1001-5515.202108066.
The eye-computer interaction technology based on electro-oculogram provides the users with a convenient way to control the device, which has great social significance. However, the eye-computer interaction is often disturbed by the involuntary eye movements, resulting in misjudgment, affecting the users' experience, and even causing danger in severe cases. Therefore, this paper starts from the basic concepts and principles of eye-computer interaction, sorts out the current mainstream classification methods of voluntary/involuntary eye movement, and analyzes the characteristics of each technology. The performance analysis is carried out in combination with specific application scenarios, and the problems to be solved are further summarized, which are expected to provide research references for researchers in related fields.
基于眼电图的眼-计算机交互技术为用户提供了一种便捷的设备控制方式，具有重大的社会意义。然而，眼-计算机交互常常受到非自主眼球运动的干扰，导致误判，影响用户体验，严重时甚至会造成危险。因此，本文从眼-计算机交互的基本概念和原理出发，梳理了当前主流的自主/非自主眼球运动分类方法，并分析了每种技术的特点。结合具体应用场景进行性能分析，进一步总结了有待解决的问题，以期为相关领域的研究人员提供研究参考。
