Motion sickness and sense of presence in a virtual reality environment developed for manual wheelchair users, with three different approaches
Bibliographic record
Abstract
Visually Induced Motion Sickness (VIMS) is a bothersome and sometimes unsafe experience, frequently experienced in Virtual Reality (VR) environments. In this study, the effect of up to four training sessions to decrease VIMS in the VR environment to a minimal level was tested and verified through explicit declarations of all 14 healthy participants that were recruited in this study. Additionally, the Motion Sickness Assessment Questionnaire (MSAQ) was used at the end of each training session to measure responses to different aspects of VIMS. Total, gastrointestinal, and central motion sickness were shown to decrease significantly by the last training session, compared to the first one. After acclimatizing to motion sickness, participants' sense of presence and the level of their motion sickness in the VR environment were assessed while actuating three novel and sophisticated VR systems. They performed up to four trials of the Illinois agility test in the VR systems and the real world, then completed MSAQ and Igroup Presence Questionnaire (IPQ) at the end of each session. Following acclimatization, the three VR systems generated relatively little motion sickness and high virtual presence scores, with no statistically meaningful difference among them for either MSAQ or IPQ. Also, it was shown that presence has a significant negative correlation with VIMS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".