Design and development of a novel 3D-printed non-metallic self-locking prosthetic arm for a forequarter amputation
Bibliographic record
Abstract
BACKGROUND: Upper limb, in particular forequarter amputations, require highly customised devices that are often expensive and underutilised. OBJECTIVES: The objective of this study was to design and develop a comfortable 3D-printed cosmetic forequarter prosthetic device, which was lightweight, cool to wear, had an elbow that could lock, matched the appearance of the contralateral arm and was completely free of metal for a specific user's needs. STUDY DESIGN: Device design. TECHNIQUE: An iterative user-centred design approach was used for digitising, designing and developing a functional 3D-printed prosthetic arm for an acquired forequarter amputation, while optimising the fit and function after each prototype. RESULTS: The cost of the final arm was 20% less expensive than a traditionally-made forequarter prostheses in Singapore. The Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST) 2.0 survey was administered, with results indicating that the 3D-printed arm was preferred due to its overall effectiveness, accurate size, ease of use and suspension. However, durability had a lower score, and the weight of the arm was 100 g heavier than the user's current prosthesis. The technique described resulted in a precise fitting and shaped forequarter prosthesis for the user. Using the user's feedback in the iterations of the design resulted in improved QUEST survey results indicating the device was effective, easy to use, perceived as lighter and more secure than the user's traditionally-made device. CONCLUSION: A fully customised cosmetic forequarter prosthesis was designed and developed using digital scanning, computer-aided design modelling and 3D printing for a specific user. These technologies enable new avenues for highly complex prosthetic design innovations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".