描述多个任务中的眼神动态特征的综合数据集
Rujeena Mathema1,2, Shamimeh M Nav1,2, Shailendra Bhandari3,4
1Department of Computer Science, OsloMet - Oslo Metropolitan University, P.O. Box 4 St. Olavs plass, 0130, Oslo, Norway.
Scientific data
|February 6, 2026
概括
这项研究引入了来自251名参与者的新的眼神动态数据集,其中包括跳动,眼和瞳孔大小. 这个资源有助于研究视觉注意力和认知科学.
科学领域:
- 认知科学 认知科学
- 神经科学是一个神经科学.
- 人与计算机的交互
背景情况:
- 眼神动态对于理解视觉注意力和认知过程至关重要.
- 现有的数据集可能缺乏全面分析所需的任务或特征的多样性.
- 高分辨率,时间标记的眼睛跟踪数据对于详细的行为研究至关重要.
研究的目的:
- 为了呈现一个全面的数据集的人类眼睛-凝视动态.
- 促进眼运动控制,感知处理,视觉注意力和认知科学等领域的研究.
- 提供一个结构化,匿名的数据集,适合各种分析应用.
主要方法:
- 收集了来自251名参与者的数据,这些参与者执行了诸如消失的萨卡德,cued的萨卡德,闪的十字架,旋转的球和自由观看等任务.
- 使用 EyeLink Portable Duo 眼球追踪器硬件,以 1000 Hz 的频率进行记录.
- 处理原始EyeLink数据格式 (EDF) 文件,以遵循SIKT伦理标准,将其结构化,匿名化数据.
主要成果:
- 一个全面的目光动态数据集,包括时间标记的目光坐标,瞳孔大小和事件分类 (固定,冲击,眼).
- 数据涵盖了与眼睛追踪研究相关的各种实验范式.
- 一个自动化管道确保了记录数据的高效处理和结构.
结论:
- 这一数据集为研究视觉注意力,认知处理和眼运动控制提供了宝贵的资源.
- 其多样化的特点和任务支持广泛的研究应用,包括辅助技术开发.
- 数据集的全面性质和遵守伦理标准使其适合推进人机交互和认知科学研究.
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