abstract

Leveraging multimodal sensory information in cybersickness prediction

Authors:

Dayoung Jeong,

Kyungsik HanAuthors Info & Claims

VRST '22: Proceedings of the 28th ACM Symposium on Virtual Reality Software and Technology

Article No.: 65, Pages 1 - 2

https://doi.org/10.1145/3562939.3565667

Published: 29 November 2022 Publication History

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Abstract

Cybersickness is one of the problems that undermines user experience in virtual reality. While many studies are trying to find ways to alleviate cybersickness, only a few have considered cybersickness through multimodal perspectives. In this paper, we propose a multimodal, attention-based cybersickness prediction model. Our model was trained based on a total of 24,300 seconds of data from 27 participants and yielded the F1-score of 0.82. Our study results highlight the potential to model cybersickness from multimodal sensory information with a high level of performance and suggest that the model should be extended using additional, diverse samples.

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Colin Groth, Jan-Philipp Tauscher, Nikkel Heesen, Steve Grogorick, Susana Castillo, and Marcus Magnor. 2021. Mitigation of Cybersickness in Immersive 360 Videos. In 2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW). IEEE, 169–177.

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Cited By

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Jeong DHan K(2024)PRECYSE: Predicting Cybersickness using Transformer for Multimodal Time-Series Sensor DataProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36595948:2(1-24)Online publication date: 15-May-2024
https://dl.acm.org/doi/10.1145/3659594
Kundu RIslam RQuarles JHoque K(2023)LiteVR: Interpretable and Lightweight Cybersickness Detection using Explainable AI2023 IEEE Conference Virtual Reality and 3D User Interfaces (VR)10.1109/VR55154.2023.00076(609-619)Online publication date: Mar-2023
https://doi.org/10.1109/VR55154.2023.00076

Index Terms

Leveraging multimodal sensory information in cybersickness prediction
1. Computing methodologies
  1. Computer graphics
    1. Graphics systems and interfaces
      1. Virtual reality
2. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI design and evaluation methods
    2. Interaction paradigms
      1. Mixed / augmented reality
      2. Virtual reality

Index terms have been assigned to the content through auto-classification.

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Published In

VRST '22: Proceedings of the 28th ACM Symposium on Virtual Reality Software and Technology

November 2022

466 pages

ISBN:9781450398893

DOI:10.1145/3562939

Editors:
Takafumi Koike
Hosei University, Japan
,
Naoya Koizumi
The University of Electro-Communications, Japan
,
Gerd Bruder
University of Central Florida, USA
,
Daniel Roth
Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
,
Kazuki Takashima
Tohoku University, Japan
,
Takefumi Hiraki
University of Tsukuba, Japan
,
Yuki Ban
The University of Tokyo, Japan
,
Michal Piovarci
Institute of Science and Technology Austria, Austria

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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 November 2022

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Institute of Information & communications Technology Planning & Evaluation (IITP)
Institute of Information & communications Technology Planning & Evaluation
Institute of Information & communications Technology Planning & Evaluation
National Research Foundation of Korea

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VRST '22

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VRST '22: 28th ACM Symposium on Virtual Reality Software and Technology

November 29 - December 1, 2022

Tsukuba, Japan

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Overall Acceptance Rate 66 of 254 submissions, 26%

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Jeong DHan K(2024)PRECYSE: Predicting Cybersickness using Transformer for Multimodal Time-Series Sensor DataProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36595948:2(1-24)Online publication date: 15-May-2024
https://dl.acm.org/doi/10.1145/3659594
Kundu RIslam RQuarles JHoque K(2023)LiteVR: Interpretable and Lightweight Cybersickness Detection using Explainable AI2023 IEEE Conference Virtual Reality and 3D User Interfaces (VR)10.1109/VR55154.2023.00076(609-619)Online publication date: Mar-2023
https://doi.org/10.1109/VR55154.2023.00076

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Abstract

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Recommendations

The presence of an avatar can reduce cybersickness in Virtual Reality

Multimodal augmented reality: the norm rather than the exception

Experimenting novel virtual-reality immersion strategy to alleviate cybersickness

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