Powered wheelchair simulator development: implementing combined navigation-reaching tasks with a 3D hand motion controller
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
BACKGROUND: Powered wheelchair (PW) training involving combined navigation and reaching is often limited or unfeasible. Virtual reality (VR) simulators offer a feasible alternative for rehabilitation training either at home or in a clinical setting. This study evaluated a low-cost magnetic-based hand motion controller as an interface for reaching tasks within the McGill Immersive Wheelchair (miWe) simulator. METHODS: Twelve experienced PW users performed three navigation-reaching tasks in the real world (RW) and in VR: working at a desk, using an elevator, and opening a door. The sense of presence in VR was assessed using the iGroup Presence Questionnaire (IPQ). We determined concordance of task performance in VR with that in the RW. A video task analysis was performed to analyse task behaviours. RESULTS: Compared to previous miWe data, IPQ scores were greater in the involvement domain (p < 0.05). Task analysis showed most of navigation and reaching behaviours as having moderate to excellent (K > 0.4, Cohen's Kappa) agreement between the two environments, but greater (p < 0.05) risk of collisions and reaching errors in VR. VR performance demonstrated longer (p < 0.05) task times and more discreet movements for the elevator and desk tasks but not the door task. CONCLUSIONS: Task performance showed poorer kinematic performance in VR than RW but similar strategies. Therefore, the reaching component represents a promising addition to the miWe training simulator, though some limitations must be addressed in future development.
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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 | 0.000 |
| 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 it