Hand rehabilitation based on the RobHand exoskeleton in stroke patients: A case series study
Bibliographic record
Abstract
Introduction: The RobHand (Robot for Hand Rehabilitation) is a robotic neuromotor rehabilitation exoskeleton that assists in performing flexion and extension movements of the fingers. The present case study assesses changes in manual function and hand muscle strength of four selected stroke patients after completion of an established training program. In addition, safety and user satisfaction are also evaluated. Methods: The training program consisted of 16 sessions; two 60-minute training sessions per week for eight consecutive weeks. During each session, patients moved through six consecutive rehabilitation stages using the RobHand. Manual function assessments were applied before and after the training program and safety tests were carried out after each session. A user evaluation questionnaire was filled out after each patient completed the program. Results: The safety test showed the absence of significant adverse events, such as skin lesions or fatigue. An average score of 4 out of 5 was obtained on the Quebec User Evaluation of Satisfaction with Assistive Technology 2.0 Scale. Users were very satisfied with the weight, comfort, and quality of professional services. A Kruskal-Wallis test revealed that there were not statistically significant changes in the manual function tests between the beginning and the end of the training program. Discussion: It can be concluded that the RobHand is a safe rehabilitation technology and users were satisfied with the system. No statistically significant differences in manual function were found. This could be due to the high influence of the stroke stage on motor recovery since the study was performed with chronic patients. Hence, future studies should evaluate the rehabilitation effectiveness of the repetitive use of the RobHand exoskeleton on subacute patients. Clinical Trial Registration: https://clinicaltrials.gov/ct2/show/NCT05598892?id=NCT05598892&draw=2&rank=1 , identifier NCT05598892.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".