Adapting Visual Complexity Based on Electrodermal Activity Improves Working Memory Performance in Virtual Reality
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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Authors
Chiossi, Francesco
Turgut, Yagiz
Welsch, Robin
Mayer, Sven
Date
2023-09-12
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Department of Computer Science
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en
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Proceedings of the ACM on Human-Computer Interaction, Volume 7, issue MHCI
Abstract
Biocybernetic loops encompass users' state detection and system adaptation based on physiological signals. Current adaptive systems limit the adaptation to task features such as task difficulty or multitasking demands. However, virtual reality allows the manipulation of task-irrelevant elements in the environment. We present a physiologically adaptive system that adjusts the virtual environment based on physiological arousal, i.e., electrodermal activity. We conducted a user study with our adaptive system in social virtual reality to verify improved performance. Here, participants completed an n-back task, and we adapted the visual complexity of the environment by changing the number of non-player characters. Our results show that an adaptive virtual reality can control users' comfort, performance, and workload by adapting the visual complexity based on physiological arousal. Thus, our physiologically adaptive system improves task performance and perceived workload. Finally, we embed our findings in physiological computing and discuss applications in various scenarios.Description
Publisher Copyright: © 2023 ACM.
Keywords
adaptive systems, electrodermal activity, physiological computing, virtual reality, visual complexity, working memory
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Citation
Chiossi, F, Turgut, Y, Welsch, R & Mayer, S 2023, ' Adapting Visual Complexity Based on Electrodermal Activity Improves Working Memory Performance in Virtual Reality ', Proceedings of the ACM on Human-Computer Interaction, vol. 7, no. MHCI, 196 . https://doi.org/10.1145/3604243