Real-time eye tracking analysis for training in a dynamic task

R. P. Fraga, Ziho Kang, Junehyung Lee, J. Crutchfield
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引用次数: 1

Abstract

A dynamic task refers to a task in which the state of the system can dynamically change when a user interacts with the system's components. For example, when an air traffic controller detects aircraft on converging flight paths, the controller can select from multiple altitude, heading and speed clearances to maintain safe separation between them. Some clearance options for those two aircraft, however, may lead to losses of separation with other aircraft. One viable non-intrusive approach to characterize a user's interaction with a system is through real-time analysis of eye movements at the time when the state of the system is changing. The presentation of data from such analyses could be an effective way to enhance user training techniques. In this article, we provide a framework of how to analyze eye-tracking data to identify useful characteristics along with associated algorithms, followed by a simple case study to validate our framework.
实时眼动跟踪分析,用于训练中的动态任务
动态任务是指当用户与系统组件交互时,系统状态可以动态改变的任务。例如,当空中交通管制员检测到飞行路径趋同的飞机时,管制员可以从多个高度、航向和速度间隙中进行选择,以保持它们之间的安全距离。然而,这两架飞机的一些间隙选择可能导致失去与其他飞机的分离。描述用户与系统交互的一种可行的非侵入性方法是通过实时分析系统状态变化时的眼球运动。提出这种分析的数据可能是加强用户培训技术的有效方法。在本文中,我们提供了一个如何分析眼动追踪数据以识别有用特征以及相关算法的框架,然后通过一个简单的案例研究来验证我们的框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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