@inproceedings{1102188128c34dcb8fa2b5622bb086c1,
title = "Predicting cognitive load in an emergency simulation based on behavioral and physiological measures",
abstract = "The reliable estimation of cognitive load is an integral step towards real-time adaptivity of learning or gaming environments. We introduce a novel and robust machine learning method for cognitive load assessment based on behavioral and physiological measures in a combined within- and crossparticipant approach. 47 participants completed different scenarios of a commercially available emergency personnel simulation game realizing several levels of difficulty based on cognitive load. Using interaction metrics, pupil dilation, eye-fixation behavior, and heart rate data, we trained individual, participant-specific forests of extremely randomized trees differentiating between low and high cognitive load. We achieved an average classification accuracy of 72%. We then apply these participant-specific classifiers in a novel way, using similarity between participants, normalization, and relative importance of individual features to successfully achieve the same level of classification accuracy in cross-participant classification. These results indicate that a combination of behavioral and physiological indicators allows for reliable prediction of cognitive load in an emergency simulation game, opening up new avenues for adaptivity and interaction.",
keywords = "Classification, Cognitive Load, Eye Tracking, Heart Rate, Multimodal",
author = "Tobias Appel and Natalia Sevcenko and Franz Wortha and Katerina Tsarava and Korbinian Moeller and Manuel Ninaus and Peter Gerjets and Enkelejda Kasneci",
note = "Publisher Copyright: {\textcopyright} 2019 Copyright held by the owner/author(s).; 21st ACM International Conference on Multimodal Interaction, ICMI 2019 ; Conference date: 14-10-2019 Through 18-10-2019",
year = "2019",
month = oct,
day = "14",
doi = "10.1145/3340555.3353735",
language = "English",
series = "ICMI 2019 - Proceedings of the 2019 International Conference on Multimodal Interaction",
publisher = "Association for Computing Machinery, Inc",
pages = "154--163",
editor = "Wen Gao and {Ling Meng}, {Helen Mei} and Matthew Turk and Fussell, {Susan R.} and Bjorn Schuller and Bjorn Schuller and Yale Song and Kai Yu",
booktitle = "ICMI 2019 - Proceedings of the 2019 International Conference on Multimodal Interaction",
}