Usability testing of multimodal feedback interface and simulated collision-avoidance power wheelchair for long-term-care home residents with cognitive impairments
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
Many older adults in long-term-care homes have complex physical and cognitive impairments and have difficulty propelling manual wheelchairs. Power wheelchair use is restricted owing to safety concerns. Power wheelchairs with collision-avoidance features are being developed to enable safe and independent mobility; however, a paucity of information exists on interface features to help users navigate away from obstacles. We developed a system combining an interface with auditory, visual, and haptic feedback and a simulated collision-avoidance power wheelchair. This device allowed the investigator to stop movement of the power wheelchair when users approached obstacles and to deliver feedback to help them navigate. Five long-term-care home residents with mild or moderate cognitive impairments evaluated device usability, which included effectiveness, efficiency, and user satisfaction. Each resident used the device for six 1 h sessions. Observations, feedback interviews, and outcome questionnaires were completed during and after the sessions. We found the device effective in enabling residents to achieve basic driving tasks and self-identified indoor mobility goals. Furthermore, residents perceived workload to be low and were satisfied with the device. Residents also felt that the feedback was useful to help them navigate away from obstacles.
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.
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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