A Tablet-Based Technology for Objective Exercise Monitoring in Vestibular Rehabilitation: Mixed Methods Study
Bibliographic record
Abstract
Background: A low-cost home exercise system called VestAid has been developed to assist participants during vestibulo-ocular reflex gaze stabilization exercises outside of clinic visits. The system includes a tablet-based app for the participant and a web-based portal for the physical therapist that provides data to make judgments about exercise accuracy and performance. Objective: The purpose of this study was to assess the feasibility and acceptability of VestAid in a pilot study of 10 participants (mean age 45 [SD 19] years; 6 women) with various vestibular diagnoses. Methods: All participants completed twelve 30-second horizontal vestibulo-ocular reflex exercises in a seated position (6 "easy" and 6 "hard" exercises). The exercises differed by variations in the background color, pattern, and movement. One of the exercises was repeated to assess the test-retest reliability of the measure of gaze stability accuracy and head motion compliance during the exercise. Participants rated the difficulty of the exercises (0-10 where 0=easy, 10=difficult) and completed usability surveys. Results: Participants completed the VestAid session without adverse events. The responses from the usability survey demonstrate the acceptability of VestAid. The mean rating of the "easy" exercises was 2.7/10 (SD 1.9). The mean rating for the "difficult" exercises across participants was 4.8/10 (SD 2.1). Conclusions: The consistency of the mean ratings of the participants with the exercise classifications ("easy" and "difficult") suggests that VestAid has clinical utility.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".