Real-time Prediction of User Performance based on Pupillary Assessment via Eye-Tracking
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...
Paper Details
Title
Real-time Prediction of User Performance based on Pupillary Assessment via Eye-Tracking
Published Date
Mar 31, 2018
Pages
26 - 60
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