Using Fuzzy Logic to Involve Individual Differences for Predicting Cybersickness during VR Navigation
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 fuzz...
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| Vydáno v: | Proceedings (IEEE Conference on Virtual Reality and 3D User Interfaces. Online) s. 373 - 381 |
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| Jazyk: | angličtina |
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IEEE
01.03.2021
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| ISSN: | 2642-5254 |
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| 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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| AbstractList | 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. |
| Author | Chardonnet, Jean-Remy Merienne, Frederic Ovtcharova, Jivka Wang, Yuyang |
| Author_xml | – sequence: 1 givenname: Yuyang surname: Wang fullname: Wang, Yuyang email: yuyang.wang@ensam.eu organization: Arts et Metiers Institute of Technology LISPEN, HESAM Université, UBFC – sequence: 2 givenname: Jean-Remy surname: Chardonnet fullname: Chardonnet, Jean-Remy email: jean-remy.chardonnet@ensam.eu organization: Arts et Metiers Institute of Technology LISPEN, HESAM Université, UBFC – sequence: 3 givenname: Frederic surname: Merienne fullname: Merienne, Frederic email: frederic.merienne@ensam.eu organization: Arts et Metiers Institute of Technology LISPEN, HESAM Université, UBFC – sequence: 4 givenname: Jivka surname: Ovtcharova fullname: Ovtcharova, Jivka email: jivka.ovtcharova@kit.edu organization: Institute for Information Management in Engineering Karlsruhe Institute of Technology |
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| Snippet | Many studies have explored how individual differences can affect users' susceptibility to cybersickness in a VR application. However, the lack of strategy to... |
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| SubjectTerms | 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 |
| Title | Using Fuzzy Logic to Involve Individual Differences for Predicting Cybersickness during VR Navigation |
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