Impacts of robotic arm use on individuals with upper extremity disabilities: A scoping review
Bibliographic record
Abstract
BACKGROUND.: Robotic arms may help users perform various activities. Even though robotic arms are commercially available, their impacts are still poorly understood. PURPOSE.: This scoping review aimed to identify the potential impacts of using robotic arms for individuals with upper-extremity disabilities and appraise the scientific quality of the selected studies. METHOD.: A search for studies published between 1970 and 2016 was conducted in PubMed, Embase, Compendex, and Scopus. The Canadian Model of Occupational Performance and Engagement was used to classify activities in which impacts were evaluated. The quality of each study was rated using McMaster University's critical review form for quantitative studies. FINDINGS.: Thirty-six studies were reviewed, which evaluated self-care (21), productivity (33), and leisure (8). The short-term impacts were more commonly documented than long-term impacts. The impacts identified were mostly positive. The studies' mean quality score was 8.8/15. IMPLICATIONS.: Additional studies with more rigorous conditions are needed to produce higher-quality scientific evidence of the long-term impacts of robotic arm use.
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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 | 0.008 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".