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Using Fuzzy Logic to Involve Individual Differences for Predicting Cybersickness during VR Navigation

Type
Communications avec actes
Author
WANG, Yuyang
543315 Laboratoire d’Ingénierie des Systèmes Physiques et Numériques [LISPEN]
CHARDONNET, Jean-Rémy
543315 Laboratoire d’Ingénierie des Systèmes Physiques et Numériques [LISPEN]
MERIENNE, Frédéric
543315 Laboratoire d’Ingénierie des Systèmes Physiques et Numériques [LISPEN]
OVTCHAROVA, Jivka
469668 Institut für Informationsmanagement im Ingenieurwesen [IMI]

URI
http://hdl.handle.net/10985/20097
DOI
10.1109/VR50410.2021.00060
Date
2021

Abstract

Many studies have explored how individual differences can affect users’ susceptibility to cybersickness in a VR application. However, the lack of strategy to integrate the influence of each factor on cybersickness makes it difficult to utilize the results of existing research. Based on the fuzzy logic theory that can represent the effect of different factors as a single value containing integrated information, we developed two approaches including the knowledge-based Mamdani-type fuzzy inference system and the data-driven Adaptive neuro-fuzzy inference system (ANFIS) to involve three individual differences (Age, Gaming experience and Ethnicity). We correlated the corresponding outputs with the simulator sickness questionnaire (SSQ) scores in a simple navigation scenario. The correlation coefficients obtained through a 4-fold cross validation were found statistically significant with both fuzzy logic approaches, indicating their effectiveness to influence the occurrence and the level of cybersickness. Our work provides insights to establish customized experiences for VR navigation by involving individual differences.

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