Assessment of Multiple Systemic Human Cognitive States using Pupillometry
Abstract
How to best and robustly detect human systemic cognitive states like workload, sense of urgency, mind wandering, interference, and others is still an open question as the answer essentially depends both on the employed physiological measurements as well as the trained computational classification models. In this paper, we analyze data from a human driving experiment to explore the validity of eye gaze in assessing different systemic cognitive states and relations among them. Our statistical analyses and classification results indicate that eye gaze, in particular the percentage change in pupil size (PCPS), is a reliable physiological biomarker in assessing multiple systemic human cognitive states including workload, sense of urgency (SoU), and mind wandering (MW) while it does not seem suitable to detect task interference (which can be assessed based on participant's response times.