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

• Published in: 2021 IEEE Virtual Reality and 3D User Interfaces (VR) pp. 373 - 381
• Main Authors: Wang, Yuyang, Chardonnet, Jean-Remy, Merienne, Frederic, Ovtcharova, Jivka
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.03.2021
• Subjects: Computing methodologies-Artificial intelligence-Knowledge representation and reasoning-Vagueness and fuzzy logic; Correlation coefficient; Cybersickness; Fuzzy logic; Human-centered computing-Human computer interaction (HCI)-Interaction paradigms-Virtual reality; Information systems-Information retrieval-Users and interactive retrieval-Personalization; Navigation; Solid modeling; Three-dimensional displays; Visualization
• DOI: 10.1109/VR50410.2021.00060

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.