iPad Technology for Home Rehabilitation after Stroke (iHOME): A Proof-of-Concept Randomized Trial
Bibliographic record
Abstract
BACKGROUND: Tablets are a novel line of computers controlled by a multitouch screen. Fine motor movements are captured on the tablet computer through electrical fields and can be qualitatively and quantitatively assessed. Evidence is limited on tablet use for stroke rehabilitation. METHODS: iHOME is an investigator-initiated randomized controlled pilot trial with a single-blinded outcome assessment. The intervention consists of iPad use (investigational group) vs. usual care (control group) among patients receiving conventional outpatient rehabilitation. Eligibility includes aged 18-85 years who experienced a mild ischemic or hemorrhagic stroke (as diagnosed on neuroimaging and determined by the Chedoke-McMaster score ≥3. The STROKE REHAB® software for the iPad was specifically designed for patients with fine motor weakness and/or neglect. Of the total 30 patients, 20 will be in iHOME Acute (enrolled within three-months of stroke onset) and 10 patients in iHOME Chronic (enrolled more than six-months from onset). OUTCOME MEASURES: The primary feasibility outcome is the proportion of the scheduled iPad time used (more than 70% (≥140 mins) of the total 'dose' of intervention intended will be considered successful). Efficacy in fine motor movements will be assessed using the nine-hole peg test; time to magnify and pop the balloons in the iPad software application, and improvement in Wolf Motor Function Test. CONCLUSIONS: iHOME is a randomized controlled trial assessing the feasibility, safety, and efficacy of tablet technology for home use in stroke rehabilitation. The results of this study will serve as the basis for a larger multicenter trial.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".