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Response time and eye tracking datasets for activities demanding varying cognitive load

机译:响应时间和眼睛跟踪数据集要求不同的认知负荷的活动

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The dataset contains the following three measures that are widely used to determine cognitive load in humans: Detection Response Task - response time, pupil diameter, and eye gaze. These measures were recorded from 28 participants while they underwent tasks that are designed to permeate three different cognitive difficulty levels. The dataset will be useful to those researchers who seek to employ low cost, non-invasive sensors to detect cognitive load in humans and to develop algorithms for human-system automation. One such application is found in Advanced Driver Assistance Systems where eye-trackers are employed to monitor the alertness of the drivers. The dataset would also be helpful to researchers who are interested in employing machine learning algorithms to develop predictive models of humans for applications in human-machine system automation. The data is collected by the authors at the Department of Electrical & Computer Engineering in collaboration with the Faculty of Human Kinetics at the University of Windsor under the guidance of their Research Ethics Board.
机译:数据集包含以下三种措施,广泛用于确定人类中的认知负荷:检测响应任务 - 响应时间,瞳孔直径和眼睛凝视。这些措施是从28名参与者记录的,而他们经历过旨在渗透三种不同的认知难度水平的任务。数据集对那些寻求使用低成本的非侵入性传感器的研究人员有用,以检测人类中的认知负荷并开发用于人机自动化的算法。一个这样的应用程序是在采用眼动员的先进驾驶员辅助系统中找到监控驱动程序的警觉性。 DataSet也对有兴趣采用机器学习算法的研究人员有所帮助,以开发人机系统自动化应用程序的预测模型。根据其研究道德委员会的指导,与Windsor大学的人类动力学系的作者在电气计算机工程系中收集。

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