ArticleSensors (Basel, Switzerland)2021
Mitigating Cybersickness in Virtual Reality Systems through Foveated Depth-of-Field Blur.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Cybersickness Variability by Race: Findings From 6 Studies and a Mini Meta-analysis.Journal of medical Internet research · 2022Pooled it
- A Study on Autonomous Driving Motion Sickness from the Perspective of Multimodal Human Signals.Sensors (Basel, Switzerland) · 2026Article
- Development of an ecological, immersive approach to socio-moral reasoning assessment in virtual reality.Frontiers in psychology · 2026Article
- Bridging Needs and Expectations of Individuals With Physical Disabilities and Community Services Stakeholders for the Cocreation of an Adapted Physical Activity Platform in Virtual Reality: Qualitative Study.JMIR serious games · 2025Article
- Clinical Feasibility of Applying Immersive Virtual Reality during Robot-Assisted Gait Training for Individuals with Neurological Diseases: A Pilot Study.Brain sciences · 2024Article
- CyPVICS: A framework to prevent or minimise cybersickness in immersive virtual clinical simulation.Heliyon · 2024Article
- Enhancing consumer sensory science approach through augmented virtuality.Current research in food science · 2024Article
- Development of a Magnetoresistive-Based Wearable Eye-Tracking System for Oculomotor Assessment in Neurological and Otoneurological Research-Preliminary In Vivo Tests.Brain sciences · 2023Article
- User Perceptions of Visual Blood: An International Mixed Methods Study on Novel Blood Gas Analysis Visualization.Diagnostics (Basel, Switzerland) · 2023Article
- Design guidelines for limiting and eliminating virtual reality-induced symptoms and effects at work: a comprehensive, factor-oriented review.Frontiers in psychology · 2023Review
- Upper limb rehabilitation system based on virtual reality for breast cancer patients: Development and usability study.PloS one · 2021Article
- Using Blur for Perceptual Investigation and Training in Sport? A Clear Picture of the Evidence and Implications for Future Research.Frontiers in psychology · 2021Review
- Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Cybersickness is one of the major roadblocks in the widespread adoption of mixed reality devices. Prolonged exposure to these devices, especially virtual reality devices, can cause users to feel discomfort and nausea, spoiling the immersive experience. Incorporating spatial blur in stereoscopic 3D stimuli has shown to reduce cybersickness. In this paper, we develop a technique to incorporate spatial blur in VR systems inspired by the human physiological system. The technique makes use of concepts from foveated imaging and depth-of-field. The developed technique can be applied to any eye tracker equipped VR system as a post-processing step to provide an artifact-free scene. We verify the usefulness of the proposed system by conducting a user study on cybersickness evaluation. We used a custom-built rollercoaster VR environment developed in Unity and an HTC Vive Pro Eye headset to interact with the user. A Simulator Sickness Questionnaire was used to measure the induced sickness while gaze and heart rate data were recorded for quantitative analysis. The experimental analysis highlighted the aptness of our foveated depth-of-field effect in reducing cybersickness in virtual environments by reducing the sickness scores by approximately 66%.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.