眼动熵：计算方法、应用场景与研究展望
Eye-movement entropy: Indicator construction, method implementation, and multidomain applications
念靖晴 1张禹 2罗禹2
作者信息
- 1. 贵州师范大学心理学院
- 2. 贵州师范大学心理学院;贵州省脑功能和脑疾病防治重点实验室
- 折叠
摘要
眼动熵是基于信息熵的客观测量指标，可从注视序列的转移模式和注视位置的空间分布两个方面量化视觉扫描行为的复杂性与不确定性，为传统眼动指标提供补充信息。其中，注视熵侧重刻画注视位置的空间分布特征，视觉注意熵侧重量化视觉注意分配的不确定性。眼动熵已用于研究视觉搜索、注意分配与个体差异，并用于评估认知状态、任务表现及身心健康。未来研究应进一步规范眼动熵的计算与报告，发展动态建模方法并拓展指标类型，以提高测量结果的稳健性与跨研究可比性。同时，还需检验各类眼动熵指标在不同任务与情境中的信度和效度，明确其适用条件与实际价值，为眼动熵在科研与实践中的应用提供依据。
Abstract
Eye-movement entropy is an information-theoretic measure of eye movement behavior. It complements conventional eye-tracking measures by quantifying the complexity and uncertainty of visual scanning based on the spatial distribution of fixations and the transitions between successive fixations. Gaze entropy characterizes how fixations are distributed across space, whereas visual attention entropy quantifies uncertainty in the allocation of visual attention. Researchers have used eye-movement entropy to investigate visual search, attentional allocation, and individual differences, and to assess cognitive states, task performance, and physical and mental health. Future research should standardize the calculation and reporting of eye-movement entropy to improve the robustness and comparability of findings across studies. Developing dynamic models and expanding the range of entropy measures would allow researchers to characterize a broader set of scanning patterns. Evaluating the reliability and validity of these measures across tasks and settings will help establish when they can be used in research and practice.关键词
眼动/注视熵/静止凝视熵/注意转移熵/视觉注意熵Key words
eye movement/gaze entropy/stationary gaze entropy/gaze transition entropy/visual attention entropy引用本文复制引用
念靖晴,张禹,罗禹.眼动熵：计算方法、应用场景与研究展望[EB/OL].(2026-11-11)[2026-11-13].https://chinaxiv.org/abs/202502.00142.学科分类
人类学
