Application of Computer Vision Techniques to Study the Relationship between Mental Stress and Pupil Diameter among Student Population

L. Moharana, Niva Das, A. Routray
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Abstract

Stress is a state of mental tension, which helps us to cope with challenges in our life. It makes us progressive when it is positive, but excessive negative stress that perseveres for a long time leads to a state of depressiveness. Longer stressed stage of a human being changes the size, functionality and frequency of response of many internal and external body parameters. By applying computer vision techniques, these changes of body parameters can be tracked to get useful information about the mental stress for a stress affected person. Many studies show the pupil diameter varies significantly with the effect of stress. Our work is based on the study of variation of pupil diameters of stress affected and not affected university students. With the application of different supervised machine learning algorithms, we have observed that the pupil dilates more in case of stress affected students than non-stressed students. We have also found that the pupils of the students dilates more when they were in positive emotional states than their negative emotional states. This work will be helpful for researchers who are working in the field of emotion detection and recognition and affective disorder analysis.
应用计算机视觉技术研究学生群体中心理压力与瞳孔直径之间的关系
压力是一种精神紧张的状态,它帮助我们应对生活中的挑战。如果压力是积极的,它会让我们不断进步,但如果压力过大并长期持续,则会导致抑郁状态。人在较长时间的压力下,身体内部和外部许多参数的大小、功能和反应频率都会发生变化。通过应用计算机视觉技术,可以跟踪这些身体参数的变化,从而获得有关受压力影响者精神压力的有用信息。许多研究表明,瞳孔直径会随着压力的影响而发生显著变化。我们的研究基于对受压力影响和未受压力影响的大学生瞳孔直径变化的研究。通过应用不同的监督机器学习算法,我们观察到,受压力影响的学生比未受压力影响的学生瞳孔扩大得更多。我们还发现,处于积极情绪状态的学生比处于消极情绪状态的学生瞳孔放大得更多。这项工作将对从事情绪检测和识别以及情感障碍分析领域的研究人员有所帮助。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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