ArticleThe Journal of imaging science and technology2020
A Pilot Study on EEG-Based Evaluation of Visually Induced Motion Sickness.
Article in The Journal of imaging science and technology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The trial behind it
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Who cites it
8 citing papers in PubMed, 30 citations in OpenAlex.
- Exploring EEG and ECG in Music Listening: A Scoping Review.Psychophysiology · 2026Article
- Enhancing User Experience in Virtual Reality Through Optical Flow Simplification with the Help of Physiological Measurements: Pilot Study.Sensors (Basel, Switzerland) · 2026Article
- Reduction in EEG theta power as a potential marker for spatial disorientation during flight.Scientific reports · 2025Article
- Investigating the impact of different road scenarios on the induction intensity of motion sickness in electric vehicle passengers.Frontiers in psychology · 2025Article
- A study on the mitigating effect of different music types on motion sickness based on EEG analysis.Frontiers in human neuroscience · 2025Article
- Combined Method Comprising Low Burden Physiological Measurements with Dry Electrodes and Machine Learning for Classification of Visually Induced Motion Sickness in Remote-Controlled Excavator.Sensors (Basel, Switzerland) · 2024Article
- Prediction and detection of virtual reality induced cybersickness: a spiking neural network approach using spatiotemporal EEG brain data and heart rate variability.Brain informatics · 2023Article
- Determining Work-Rest Schedules for Visual Tasks That Use Optical Head-Mounted Displays Based on Visual Fatigue and Visually Induced Motion Sickness Recovery.International journal of environmental research and public health · 2023Article
Corrections and comments
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Authors and funding
5 authors at 4 institutions in 2 countries.
Funding
Abstract
The most prominent problem in virtual reality (VR) technology is that users may experience motion sickness-like symptoms when they immerse into a VR environment. These symptoms are recognized as visually induced motion sickness (VIMS) or virtual reality motion sickness (VRMS). The objectives of this study were to investigate the association between the electroencephalogram (EEG) and subjectively rated VIMS level (VIMSL) and find the EEG markers for VIMS evaluation. In this study, a VR-based vehicle-driving simulator (VDS) was used to induce VIMS symptoms, and a wearable EEG device with four electrodes, the Muse, was used to collect EEG data of subjects. Our results suggest that individual tolerance, susceptibility, and recoverability to VIMS varied largely among subjects; the following markers were shown to be significantly different from no-VIMS and VIMS states (P < 0.05): (1) Means of gravity frequency (GF) for theta@FP1, alpha@TP9, alpha@FP2, alpha@TP10, and beta@FP1; (2) Standard deviation of GF for alpha@TP9, alpha@FP1, alpha@FP2, alpha@TP10, and alpha@(FP2-FP1); (3) Standard deviation of power spectral entropy (PSE) for FP1; (4) Means of Kolmogorov complexity (KC) for TP9, FP1, and FP2. These results also demonstrate that it is feasible to perform VIMS evaluation using an EEG device with a small number of electrodes.
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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.