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Dummy eye measurements of microsaccades: testing the influence of system noise and head movements on microsaccade detection in a popular video-based eye tracker

机译:微扫视的假眼测量:在基于视频的流行眼动仪中测试系统噪声和头部运动对微扫视检测的影响

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摘要

Whereas early studies of microsaccades have predominantly relied on custom-built eye trackers and manual tagging of microsaccades, more recent work tends to use video-based eye tracking and automated algorithms for microsaccade detection. While data from these newer studies suggest that microsaccades can be reliably detected with video-based systems, this has not been systematically evaluated. I here present a method and data examining microsaccade detection in an often used video-based system (the Eyelink II system) and a commonly used detection algorithm (Engbert & Kliegl, 2003; Engbert & Mergenthaler, 2006). Recordings from human participants and those obtained using a pair of dummy eyes, mounted on a pair of glasses either worn by a human participant (i.e., with head motion) or a dummy head (no head motion) were compared. Three experiments were conducted. The first experiment suggests that when microsaccade measurements make use of the pupil detection mode, microsaccade detections in the absence of eye movements are sparse in the absence of head movements, but frequent with head movements (despite the use of a chin rest). A second experiment demonstrates that by using measurements that rely on a combination of corneal reflection and pupil detection, false microsaccade detections can be largely avoided as long as a binocular criterion is used. A third experiment examines whether past results may have been affected by possible incorrect detections due to small head movements. It shows that despite the many detections due to head movements, the typical modulation of microsaccade rate after stimulus onset is found only when recording from the participants’ eyes.
机译:尽管对微扫视镜的早期研究主要依赖于定制的眼动仪和对微扫视镜的手动标记,但最近的工作却倾向于使用基于视频的眼动追踪和自动算法进行微扫视镜检测。尽管来自这些较新研究的数据表明可以使用基于视频的系统可靠地检测微扫视,但尚未对此进行系统评估。我在这里介绍了一种方法和数据,用于检查经常使用的基于视频的系统(Eyelink II系统)和常用的检测算法(Engbert&Kliegl,2003; Engbert&Mergenthaler,2006)中的微扫视检测。比较了来自人类参与者的记录和使用一对假人获得的,安装在由人类参与者(即头部运动)或假人头(无头部运动)戴的眼镜上的记录。进行了三个实验。第一个实验表明,当微扫视测量使用瞳孔检测模式时,在没有眼动的情况下进行微扫视的检测稀疏,但没有头部运动,但经常发生头部运动(尽管使用了下巴托)。第二个实验表明,通过使用依赖于角膜反射和瞳孔检测的组合的测量,只要使用双目标准,就可以在很大程度上避免错误的微扫视检测。第三个实验检查过去的结果是否可能由于小头部移动而可能被错误检测而受到影响。它表明,尽管由于头部移动而进行了许多检测,但只有在从参与者的眼睛进行记录时,才能发现刺激发作后微扫视速率的典型调制。

著录项

  • 作者

    Hermens Frouke;

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  • 年度 2015
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  • 原文格式 PDF
  • 正文语种 {"code":"en","name":"English","id":9}
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