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Predicting Properties of Cognitive Pupillometry in Human–Computer Interaction: A Preliminary Investigation

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Information Systems and Neuroscience

Abstract

This paper aims to investigate the predictive property of pupil dilation in an IT-related task. Previous work in the field of cognitive pupillometry has established that pupil size is associated with cognitive load. We conducted a within-subject experiment with 22 children aged between 7 and 9. For the hard questions, visit duration, pupil size and its quadratic effect were significant predictors. We discuss the potential of using this unobtrusive approach for neuro-adaptive and auto-adaptive applications.

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Notes

  1. 1.

    http://gizmodo.com/msi-s-eye-tracking-laptop-is-the-future-but-not-the-pr-1758485727.

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Léger, PM., Charland, P., Sénécal, S., Cyr, S. (2018). Predicting Properties of Cognitive Pupillometry in Human–Computer Interaction: A Preliminary Investigation. In: Davis, F., Riedl, R., vom Brocke, J., Léger, PM., Randolph, A. (eds) Information Systems and Neuroscience. Lecture Notes in Information Systems and Organisation, vol 25. Springer, Cham. https://doi.org/10.1007/978-3-319-67431-5_14

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