Usability of mechanical assistive technologies for performing activities involving the upper extremities in individuals with impairments: a systematic review
Bibliographic record
Abstract
Purpose To conduct a systematic review on the impacts of using mechanical assistive devices on function, performance in activities and participation of persons with upper extremity impairments, and to synthesize the strengths and limitations of these devices.Method Three independent reviewers conducted systematic searches of articles published between 2003 and 2023 in Compendex, Inspec, Embase, PubMed/Medline, IEEE Xplore, and Web of Science, as well as manual searches on the RESNA website for conference papers over the same period. The methodological quality of articles was appraised using the QualSyst tool.Results From the 34 retained studies, 28 mechanical devices were identified and classified into two categories: (1) mobile arm supports (MASs) designed to perform multiple activities, and (2) devices used to assist with a specific activity of daily living (ADL). Overall, MASs helped users to perform manual activities in elevation and/or against gravity. Specific ADL devices allowed users to perform unique activities requiring fine motor skills such as opening a medicine container. Some of these devices have advantages like portability, adaptability, low cost, and ease of use. Limitations most often reported included interference or mobility restraints.Conclusion This review synthesizes the impacts of mechanical devices on the three domains of the International Classification of Functioning, Disability and Health (ICF) for individuals with upper extremity impairments. Impacts regarding function and performance in activities were more often measured than participation. Future studies should include outcomes related to participation, as taking this aspect into account might favor successful continued use of assistive devices.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".