度指标可以告诉我们眼睛固定轨迹的特征是什么?

度指标可以告诉我们眼睛固定轨迹的特征是什么?

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Kateryna Melnyk¹, Lee Friedman¹, Oleg V Komogortsev¹

¹Department of Computer Science, Texas State University, San Marcos, TX, United States of America.

PloS one

|January 2, 2024

概括

应用于眼动数据的值测量揭示了数据集特定的模式. 使用六个指标对固定轨迹的分析在不同数据集中确定了独特的固定特征,突出了眼动分类的变化.

科学领域:

眼科和计算神经科学
分析眼睛运动数据和固定特征.

背景情况:

眼动分析对于理解视觉注意力和神经疾病至关重要.
度措施提供了一种定量方法来描述眼睛运动轨迹的复杂性.

研究的目的:

在三个不同的数据集中分析固定眼睛运动轨迹的度.
调查六个度指标在识别不同类型的固定行为中的实用性.

主要方法:

计算六个度指标 (模糊,增量,样本,网格分布,相位和光谱度).
将这些指标应用于来自GazeCom,Lund和OK Lab数据集的固定数据.
检查每个数据集中具有最高和最低值的固定.

主要成果:

值指标的性能在数据集之间差异很大.
在GazeCom和Lund数据集中,特定的指标识别了错误分类的固定,线性漂移和"颠"的固定 (低频振荡).
在OK Lab数据集中检测到高频噪声,潜在的眼睛微震和线性漂移.

结论:

对眼动数据的度测量的解释是依赖于数据集的.
透分析可以揭示固定的微妙特征,包括噪音和漂移,与眼动分类相关.
数据集大小,刺激和分类方法的差异影响了基于的发现.

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