BalanceVR: Balance Training to Increase Tolerance to Cybersickness in Immersive Virtual Reality
August 10, 2023 Β· Declared Dead Β· π Virtual Reality
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Seonghoon Kang, Yechan Yang, Gerard Jounghyun Kim, Hanseob Kim
arXiv ID
2308.05276
Category
cs.HC: Human-Computer Interaction
Citations
9
Venue
Virtual Reality
Last Checked
4 months ago
Abstract
Cybersickness is a serious usability problem in virtual reality. Postural (or balance) instability theory has emerged as one of the major hypotheses for the cause of cybersickness. In this paper, we conducted a two-week-long experiment to observe the trends in user balance learning and sickness tolerance under different experimental conditions to analyze the potential inter-relationship between them. The experimental results have shown, aside from the obvious improvement in balance performance itself, that accompanying balance training had a stronger effect of increasing tolerance to cybersickness than mere exposure to VR. In addition, training in immersive VR was found to be more effective than using the 2D-based non-immersive medium, especially for the transfer effect to other non-training VR content.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted