应用随机森林检测认知分心时考虑眼球运动类型

Hiroaki Koma, Taku Harada, Akira Yoshizawa, H. Iwasaki
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引用次数: 5

摘要

众所周知,眼球运动是认知分心的表现。检测认知分心有助于预防与工作有关的事故;因此,利用眼球运动来检测认知分心是非常有用的。眼球运动可分为多种类型。在本文中,我们应用了一种考虑眼球运动类型的基于识别的机器学习算法。我们采用随机森林作为机器学习算法。我们展示了在应用随机森林检测认知分心时考虑眼球运动类型的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Considering eye movement type when applying random forest to detect cognitive distraction
Eye movements are well known to express cognitive distraction. Detecting cognitive distraction can help to prevent work-related accidents; thus, it is very useful to detect cognitive distraction using eye movements. Eye movements can be classified into various types. In this paper, we apply an identification-based machine learning algorithm considering eye movement types. We apply Random Forest as the machine learning algorithm. We show the effectiveness of considering eye movement types when applying Random Forest to detect cognitive distraction.
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