Using a 3D hand motion controller for reaching tasks in a powered wheelchair simulator
Bibliographic record
Abstract
Reaching for objects is essential in powered wheelchair (PW) mobility. For PW users, learning how to navigate their PW to reach for objects safely, as in daily activities, is crucial to their quality of life. Training for such PW use is limited due to lack of dedicated space, time, or equipment. Addressing these issues, the McGill Immersive Wheelchair (miWe) simulator is a virtual reality (VR) system for teaching PW driving skills that runs on an ordinary computer. However, a practical and low-cost training tool for reaching tasks does not exist for the miWe or any other PW simulator. Objective: The purpose of this study was to evaluate a $150 3D hand motion controller (Razer Hydra, Sixense, USA), as an interface for training reaching tasks within the miWe. This device allows 3D control of a virtual cursor with hand/arm movements. Method: Twelve experienced PW users performed three combined PW navigation and reaching tasks both in the real world (RW) and in the miWe: working at a desk, operating an elevator, and opening a door. First, we determined concordance of task performance in VR with that in the RW. Total task time, time spent reaching, number of joystick movements, and number of reaching movements were measured. A video task analysis was also performed. Second, the sense of presence in VR was assessed using the iGroup Presence Questionnaire (IPQ). Third, participants gave feedback in an open questionnaire. Results: Tasks performed in VR demonstrated significantly (p<0.05, Wilcoxon Sign-Rank) longer task times and greater number of movements for the elevator and desk tasks but not the door task. Task analysis revealed significantly greater (p<0.05) risk of collisions and reaching errors in VR compared to RW tasks. The majority of navigation and reaching behaviours showed moderate to excellent (K > 0.4, Cohen's Kappa) agreement between the two environments. IPQ scores demonstrated a significant (p < 0.05) increase in "involvement" while "general sense of presence", "spatial presence", and "realism" remained the same compared to previously collected miWe data. Participants generally perceived the tasks and the reaching component to be useful, but noted difficulties with joystick control and software glitches. Conclusions: Task performance showed poorer kinematic performance in VR than RW overall, but similar strategies. While the reaching component represents a promising addition to the miWe simulator, important limitations must be addressed for this VR simulator to be an effective tool for training PW navigation-reaching tasks.
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 | 0.001 | 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".