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Measuring Mental Effort via Entropy in VR

Published: 17 March 2020 Publication History

Abstract

Recognizing changes in users' experienced mental effort is a perennial interest in human-computer interaction research particularly in the design of intelligent user interfaces built to adapt to different levels of mental effort. With virtual reality (VR) applications, for example, many measures of mental workload (e.g., secondary tasks) are highly intrusive and can distort what is being measured. In this paper we investigate the entropy of controller movements as an indicator of mental effort that can be measured unobtrusively. We report a proof-of-concept study that manipulates the experienced mental effort using the popular e-crossing task. As expected, the results show that entropy is increased for people with higher mental effort than for people with lower mental effort and that there is a positive relationship with NASA-TLX scores, the benchmark questionnaire for mental effort. Thus, intelligent user interfaces become capable of detecting mental effort in VR on the basis of controller entropy and could recognize when users need assistance in their decision making.

References

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Sandra G. Hart and Lowell E. Staveland, 1988. Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research. Advances in Psychology, 52, 139--183.
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John H. Lurquin and Akira Miyake. 2017. Challenges to ego-depletion research go beyond the replication crisis: a need for tackling the conceptual crisis. Frontiers in Psychology, 8, 568.
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Daniel Reinhardt and Jörn Hurtienne. 2018. Cursor Entropy Reveals Decision Fatigue. In Proceedings of the 23rd International Conference on Intelligent User Interfaces Companion (IUI '18 Companion). ACM, New York, NY, Article 31, 1--2.
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Claude E. Shannon. 2001. A mathematical theory of communication. ACM SIGMOBILE Mobile Computing and Communications Review 5, 1: 3--55.
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Jeffrey W. Sherman, Bertram Gawronski, and Yaacov Trope. 2014. Dual-process theories of the social mind. Guilford Publications, New York, NY.
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Weihong Wang, Zhidong Li, Yang Wang, and Fang Chen. 2013. Indexing cognitive workload based on pupillary response under luminance and emotional changes. In Proceedings of the 2013 International Conference on Intelligent User Interfaces (IUI '13). ACM, New York, NY, 247--256.

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  • (2023)Measuring Intuitive Use: Theoretical FoundationsInternational Journal of Human–Computer Interaction10.1080/10447318.2023.216620440:10(2453-2483)Online publication date: 25-Jan-2023

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    cover image ACM Conferences
    IUI '20 Companion: Companion Proceedings of the 25th International Conference on Intelligent User Interfaces
    March 2020
    153 pages
    ISBN:9781450375139
    DOI:10.1145/3379336
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    New York, NY, United States

    Publication History

    Published: 17 March 2020

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    Author Tags

    1. Entropy
    2. Evaluation
    3. Mental Workload

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    • (2023)Measuring Intuitive Use: Theoretical FoundationsInternational Journal of Human–Computer Interaction10.1080/10447318.2023.216620440:10(2453-2483)Online publication date: 25-Jan-2023

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