A Pilot Feasibility Trial of an Upper Extremity Assistive System
Bibliographic record
Abstract
Objective: To develop and clinically evaluate a customizable active upper extremity (UE) assistive system with integrated functional electrical stimulation (FES) that improves function and independence of individuals during activities of daily living (ADLs). Design: Single-arm, prospective, open-label cohort feasibility trial. Setting: An academic research institution. Participants: Subjects were 5 adults with a medical history of stroke resulting in distal UE impairment (N=5). The subjects volunteered from recruitment materials that detailed information about the study. Interventions: A novel, wearable, lightweight, low-profile, and patient-tailored UE assistive system. It comprises a splint component and FES unit that may each be controlled by electromyography (EMG) signals, inertial measurement units (IMUs), manual control source (joystick), and/or voice control. Main Outcome Measures: Several occupational therapy outcome measures were used, including the Canadian Occupational Performance Measure (COPM), Action Research Arm Test (ARAT), The Box and Blocks Test (BBT), the ABILHAND-Manual Ability Measure, and Patient Reported Outcomes Measurement Information System (PROMIS) UE Short Form. Results: All participants learned to use our UE assistive system to perform ADLs and were able to use it independently at home. Most participants experienced a clinically meaningful improvement in both performance and satisfaction for the majority of their COPM goals while using the system. All participants experienced improvement in hand grip and release as shown by their baseline and post assessment scores for hand function (BBT, ARAT) and patient-reported outcomes (ABILHAND, PROMIS). Conclusions: The clinical outcomes suggest that our UE assistive system improves functional performance in patients with UE impairment, allowing them to engage more actively in ADLs. Further innovation including elbow and shoulder components will allow users to have more degrees of freedom during tasks.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".