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The use of eye metrics to index cognitive workload in video games

机译:使用眼睛指标来索引视频游戏中的认知工作量

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Eye tracking metrics may provide unobtrusive measures of cognitive states such as workload and fatigue and can serve as useful inputs into future human computer interface technologies. To further explore the usefulness of eye tracking for the estimation of cognitive state, the current experiment evaluated saccade, fixation, and pupil-based measures to identify which metrics reliably indexed cognitive workload in a dynamic, unconstrained task (Tetris®). In line with previous studies, our results show that some eye movement features are correlated with changes in workload, manipulated here via task difficulty. Among these were blink duration, saccade velocity, and tonic pupil dilation.
机译:眼睛跟踪指标可以提供对认知状态(例如工作量和疲劳)的不干扰性的度量,并且可以用作将来的人机界面技术的有用输入。为了进一步探索眼动追踪对认知状态估计的有用性,当前实验评估了扫视,注视和基于学生的测量,以识别哪些指标可以可靠地索引动态,无限制任务中的认知工作量(Tetris®)。与以前的研究一致,我们的结果表明,某些眼球运动特征与工作量变化相关,在此可通过任务难度来操纵。其中包括眨眼时间,扫视速度和强直瞳孔扩张。

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