Open-source 3D printable forearm crutch
Bibliographic record
Abstract
Although there has been considerable progress in distributed manufacturing of open-source designs for mobility aids, there is a notable lack of affordable, open-source crutches. Crutches are a vital tool for many individuals with mobility impairments, yet the high costs limit accessibility. Even more, they are in short supply in regions undergoing conflict. The goal of this study is to address this need by leveraging the principles of free and open-source hardware and the capabilities of digital distributed manufacturing to create a low-cost, functional crutch that can be easily produced and customized locally using inexpensive desktop 3D printers. All the design files are open-source, and the design process incorporated load-bearing tests using a hydraulic actuator under static loading conditions to meet the ISO 11334-1:2007 standard for walking aids. The open-source forearm crutch developed in this study not only surpasses the requirements of the ISO method for load capacity (1,516.3 ± 169.9 N, which is 51.6% percent above needs), weighs a fraction of comparable commercial systems (0.612 kg or 27% of proprietary devices), and is customizable, but also offers a highly cost-effective solution; costing CAD $36 in material, which is less than all equivalent crutches on the open market. If recycled plastic is used, the material cost of the crutch could be further reduced to under CAD $13, making it much more accessible.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.029 | 0.011 |
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".