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Exploring Eye Activity as an Indication of Emotional States Using an Eye-Tracking Sensor

机译:使用眼动追踪器探索眼睛活动作为情绪状态的指示

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The automatic detection of human emotional states has been of great interest lately for its applications not only in the Human-Computer Interaction field, but also for its applications in psychological studies. Using an emotion elic-itation paradigm, we investigate whether eye activity holds discriminative power for detecting affective states. Our emotion elicitation paradigm includes induced emotions by watching emotional movie clips and spontaneous emotions elicited by interviewing participants about emotional events in their life. To reduce gender variability, the selected participants were 60 female native Arabic speakers (30 young adults, and 30 mature adults). In general, the automatic classification results using eye activity were reasonable, giving 66% correct recognition rate on average. Statistical measures show statistically significant differences in eye activity patterns between positive and negative emotions. We conclude that eye activity, including eye movement, pupil dilation and pupil invisibility could be used as a complementary cues for the automatic recognition of human emotional states.
机译:近年来,自动检测人的情绪状态不仅在人机交互领域中的应用,而且在心理学研究中的应用都引起了人们的极大兴趣。使用情感启发范式,我们调查眼睛活动是否具有判别能力以检测情感状态。我们的情绪激发范例包括通过观看情绪影片剪辑诱发的情绪,以及通过采访参与者关于其生活中发生的情绪事件而诱发的自发情绪。为了减少性别差异,选定的参与者为60位以阿拉伯语为母语的女性(30位年轻成年人和30位成熟成年人)。通常,使用眼睛活动进行自动分类的结果是合理的,平均正确识别率达到66%。统计指标显示,在积极情绪和消极情绪之间的眼部活动模式有统计学意义的差异。我们得出的结论是,眼活动,包括眼运动,瞳孔散大和瞳孔不可见,可以用作自动识别人类情绪状态的补充线索。

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