Outcomes of the NuroSleeve and Occupational Ther e and Occupational Therapy on Upper y on Upper Limb Function of an Individual with Chronic Hemiparesis Following a Stroke: A Case Report
Bibliographic record
Abstract
Background: Upper limb neuromuscular impairments can adversely impact function. This case report investigates the process and outcomes of occupational therapy (OT) for training in the use of the NuroSleeve, a novel research-grade exoskeletal powered orthosis, with a participant with chronic right hemiparesis following a stroke. Method: The participant engaged in 24 OT sessions using the NuroSleeve over 10 weeks. Therapeutic interventions included neuromuscular reeducation, device management, and engagement in occupationbased activities with training to use the NuroSleeve. The Canadian Occupational Performance Measure (COPM), ABILHAND, Patient Reported Outcomes Measurement Information System Upper Extremity Short Form 7a (PROMIS UE SF), Action Research Arm Test (ARAT), and Manual Muscle Testing (MMT) were administered before and after the 24 sessions. Results: With the NuroSleeve, there were clinically important increases in COPM performance and satisfaction for 6/8 and 7/8 goals, respectively; ABILHAND showed a clinically important increase of 4.959 logits; and there was an 11-point increase on the ARAT, indicating a clinically important difference. T-score on the PROMIS UE SF was 33.7 (SD = 2) compared to 23 (SD = 2.8) without the device. MMT remain unchanged. Conclusion: The data suggest that the NuroSleeve was the primary source of increased function and that incorporating OT with the NuroSleeve has benefits.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".