Real-time Prediction of User Performance based on Pupillary Assessment via Eye Tracking
Faculty/Professorship: | Information Systems and Services |
Author(s): | Buettner, Ricardo; Sauer, Sebastian; Maier, Christian ![]() |
Title of the Journal: | AIS Transactions on Human-Computer Interaction |
ISSN: | 1944-3900 |
Publisher Information: | AIS eLibrary |
Year of publication: | 2018 |
Volume: | 10 |
Issue: | 1 |
Pages: | 26-56 |
Language(s): | English |
DOI: | 10.17705/1thci.00103 |
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. |
Type: | Article |
URI: | https://fis.uni-bamberg.de/handle/uniba/45074 |
Year of publication: | 7. January 2019 |

originated at the
University of Bamberg
University of Bamberg