Real-time Prediction of User Performance based on Pupillary Assessment via Eye Tracking

Authors

Ricardo Buettner, Aalen UniversityFollow
Sebastian Sauer, FOM University of Applied Sciences for Economics and ManagementFollow
Christian MaierFollow
Andreas Eckhardt, German Graduate School of Management & Law (GGS)Follow

Abstract

We propose a method to predict user performance based on eye-tracking. The method uses eye-tracking-based pupillometry to capture pupil diameter data and calculates—based on a Random Forest algorithm—user performance expectations. We conducted a large-scale experimental evaluation (125 participants aged from 21 to 61 years) and found promising results that pave the way for a dynamic real-time adaption of IT to a user’s mental effort and expected user performance. We have already achieved a good classification accuracy of user performance after only 40 seconds (5% of the mean total trial time that our participants took to complete our experiment). The non-invasive contact-free method can be applied cost-efficiently both in research and practical environments.

DOI

10.17705/1thci.00103

Recommended Citation

Buettner, R., Sauer, S., Maier, C., & Eckhardt, A. (2018). Real-time Prediction of User Performance based on Pupillary Assessment via Eye Tracking. AIS Transactions on Human-Computer Interaction, 10(1), 26-56. https://doi.org/10.17705/1thci.00103
DOI: 10.17705/1thci.00103