Effects of Opacity of Peripheral Real Scene and Field of View of Mixed Reality on Motion Sickness
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Mixed reality (MR) technology enables seamless transitions between virtual and real environments, but motion sickness (MS) remains an important barrier to widespread adoption. This study investigated how opacity of peripheral real scenes (OPRS) and field of view (FoV) affect MS symptoms in MR environments where dynamic virtual content is presented centrally while static real-world scenes remain visible peripherally. A between-subjects experiment was conducted with 120 participants experiencing a 10-minute roller coaster simulation in MR. The experiment employed a 4 × 3 factorial design with four OPRS levels (0, 0.25, 0.75, and 1) and three FoV levels (30°, 60°, and 90°). Heart rate variability (HRV) was measured using electrocardiography (ECG) to assess physiological responses, and subjective MS was evaluated using the Virtual Reality Sickness Questionnaire (VRSQ). OPRS significantly influenced MS symptoms. Higher OPRS conditions showed increased sympathetic nervous system activation and decreased parasympathetic activity compared to lower OPRS levels, indicating heightened MS. FoV also showed significant effects, with the 90° condition indicating reduced MS symptoms compared to 60°. This finding is contrary to traditional VR studies, which generally report that narrower FoV reduce MS. No significant OPRS × FoV interactions were observed. These results indicate that carefully adjusting the ratio between virtual and real content visibility, particularly OPRS, is essential for developing comfortable MR interfaces.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it