Abstract
Cybersickness is a well-known issue that creates barriers to the broad usage of virtual reality (VR) in real-life scenarios. It is essential to explore the factors influencing cybersickness and intervention strategies to alleviate cybersickness. In this study, social interaction is considered a potentially promising approach to addressing cybersickness. A total of 30 participants were recruited to join both social and solitary experimental tasks in VR experiments. The subjective and objective experiences in relation to cybersickness in VR were collected. The results indicated that social interaction could mitigate the sense of cybersickness. Significant differences were observed in verbally rated cybersickness, physiological measurements, and machine learning classifications. Random forest models were constructed to classify the severity of VR cybersickness and identify the feature importance in detecting cybersickness. This study is the first to explore the role of social interaction in VR cybersickness and raises new possibilities for researchers and designers to address this issue.
Original language | English |
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Article number | 102512 |
Journal | Displays |
Volume | 80 |
DOIs | |
Publication status | Published - Dec 2023 |
Keywords
- Cybersickness
- Machine learning
- Psychophysiological measurement
- Social interaction
- Virtual reality
ASJC Scopus subject areas
- Human-Computer Interaction
- Hardware and Architecture
- Electrical and Electronic Engineering