“Connecting patients and therapists remotely using technology is feasible and facilitates exercise adherence after stroke”
Bibliographic record
Abstract
Purpose: Repetitive task practice after stroke is important to improve function, yet adherence to exercise is low. The aim of this study was to determine whether using the internet, a tablet application, and a chair sensor that connected to a therapist was feasible in monitoring adherence and progressing a functional exercise at home.Methods: Ten participants with stroke completed a 4-week sit-to-stand exercise using the technology at home (ACTRN12616000051448). A therapist remotely monitored exercise adherence, progressed goals, and provided feedback via the app. Measures of feasibility (design, recruitment/withdrawals, adherence, safety, participant satisfaction and estimates of effect on function) were collected.Results: Participants' mean age was 73.6 years [SD 9.9 years]. The system was feasible to deliver and monitor exercise remotely. All participants completed the study performing a mean 125% of prescribed sessions and 104% of prescribed repetitions. Participants rated the system usability (78%), enjoyment (70%) and system benefit (80%) as high. No adverse events were reported. The mean pre- and post-intervention difference in the total short performance physical battery score was 1.4 (95% CI 0.79, 2.00).Conclusions: It was feasible and safe to prescribe and monitor exercises using an app and sensor-based system. A definitive trial will determine whether such technology could facilitate greater exercise participation after stroke.
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 | 0.000 | 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 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".