Evidence map›Paper›PMID 41620499›Full record

ArticleScientific reports2026

Cybersickness-induced EEG responses in curved monitor and head-mounted display.

Dong-Hyun Lee, Kyoung-Mi Jang, Hyun Kyoon Lim

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Dong-Hyun LeeDivision of Biomedical Metrology, Korea Research Institute of Standards and Science (KRISS), Daejeon, 34113, Republic of Korea.
Kyoung-Mi JangDigital Heath Research Division, Korea Institute of Oriental Medicine (KIOM), Daejeon, 34054, Republic of Korea.
Hyun Kyoon LimDivision of Biomedical Metrology, Korea Research Institute of Standards and Science (KRISS), Daejeon, 34113, Republic of Korea. hlim@kriss.re.kr.

Funding

Ministry of Trade, Industry and Energy P0001940
6 · The paper itself

Abstract

Cybersickness is a common issue in virtual reality (VR), yet addressing it remains challenging due to the lack of quantitative evaluation methods. To quantitatively assess cybersickness, this study examined electroencephalography (EEG) changes and Simulator Sickness Questionnaire (SSQ) scores using two different display types: a curved monitor and a head-mounted display (HMD). Thirty-one male participants (25.0 ± 1.9 years old) were exposed to cybersickness-inducing VR content developed using the Unity engine, featuring pitch, yaw, and roll rotations.The results revealed two key findings. First, regarding cybersickness induction, both display conditions showed significant increases in Delta power and decreases in Alpha power compared to the baseline, thus validating the effectiveness of the stimulus. Second, in the direct comparison between the two displays, no statistically significant differences were found in EEG spectral power. However, SSQ scores showed significantly higher Disorientation in the HMD condition. Furthermore, no linear correlation was observed between EEG and SSQ scores.In conclusion, these findings suggest that although both displays trigger similar physiological responses associated with sensory conflict processing (EEG), the immersive HMD environment induces greater vestibular disorientation (SSQ). This implies that a curved monitor may be a viable alternative for studying the physiological correlates of cybersickness.

Indexed as

ElectroencephalographyMotion SicknessVirtual RealityAdultHeadHumansMaleSurveys and QuestionnairesYoung AdultCybersicknessElectroencephalographyVirtual reality

Identifiers

PMID41620499
PMCPMC12860796

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Registered trials

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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.