A Resource-Efficient, High-Dose, Gamified Neurorehabilitation Program for Chronic Stroke at Home: Retrospective Real-World Analysis
Bibliographic record
Abstract
Background: Accumulating evidence and medical guidelines recommend high-dose neurorehabilitation for recovery after stroke. The reality, however, is that most patients receive a fraction of this dose, with therapist availability and costs of delivery being major implementational barriers. Objective: This study aimed to explore a potential solution by conducting a retrospective analysis of a real-world enhanced clinical service that used gamified self-training technologies at home under remote therapist supervision. Methods: Data from 17 patients who completed a 12-18 week full-body, high-dose neurorehabilitation program entirely at home were analyzed. Program delivery relied primarily on patients training independently (asynchronously) with the MindMotion GO (MindMaze) gamified-therapy solution. Accompanying telerehabilitation training sessions with a therapist occurred weekly while therapists used a web application to continuously monitor and manage the program remotely. Effectiveness of the program was assessed through measured active training time, a measure that more closely reflects delivered dosage as opposed to scheduled dose. Patient recovery was evaluated with standardized impairment and functional clinical measures and patient self-reported outcome measures. Finally, a cost model was computed to evaluate the resource efficiency of the program. Results: Patients maintained high training adherence throughout the program and reached an average total active training time of 39.7 (SD 21.4) hours, with the majority delivered asynchronously (mean 82.2%, SD 10.8%). Patients improved in both upper-limb (Fugl-Meyer Upper Extremity, mean 6.4, SD 5.1; P<.001) and gait and balance measures (Functional Gait Assessment, mean 3.1, SD 2.6; P<.001; Berg Balance Scale, mean 6.1, SD 4.4; P<.001). Overall, the program was viewed very favorably among patients who completed a post-program survey, with 73.7% (14/19) of respondents being satisfied or very satisfied, while 63.2% (12/19) of respondents reported subjective improvements in physical abilities. Per-patient therapist costs approximated US $338, representing a resource-efficient alternative to delivering the same dose via one-on-one in-person training sessions (US $1903). Conclusions: This work demonstrates effective high-dose neurorehabilitation delivery via gamified therapy technologies at home. The approach shows that training time can be successfully decoupled from therapist-presence without compromising adherence, outcomes, or patient satisfaction over an extended program period. Given growing concerns over therapist availability and increasing health care costs, this resource-efficient approach can help achieve medical guidelines and complement existing clinic-based approaches.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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".