Shaping the Future of Upper Extremity Prostheses Through 3D Printing
Bibliographic record
Abstract
Introduction: Additive manufacturing has emerged as a promising solution for improving the accessibility and affordability of upper limb prostheses. Despite the growing need, traditional prosthetic devices remain costly and often inaccessible, particularly in underserved regions. This review examines the current landscape of 3D-printed upper limb prostheses, focusing on their design, functionality, and cost-effectiveness. It aims to assess the potential of 3D-printing upper limb prostheses in addressing current accessibility barriers. Methods: A two-phase approach was used to analyze the literature on 3D-printed upper limb prostheses. The first phase involved a literature search using keywords related to 3D printing and upper limbs prostheses. The second phase included data collection from online platforms such as Enabling the Future, Thingiverse, and NIH 3D Print Exchange. Studies focusing on the design, fabrication, and clinical application of 3D-printed prostheses were included. The results were organized into categories based on design characteristics, kinematic features, and manufacturing specifications. Results: A total of 35 3D-printed upper limb prostheses were reviewed, with the majority being hand prostheses. Devices were categorized based on their range of motion, actuation mechanism, materials, cost, and assembly complexity. The e-NABLE open-source platform has played a significant role in the development and dissemination of these devices. Prostheses were classified into cost categories (low, moderate, and high), with 64% of models costing under USD 50. Most designs were rated as easy to moderate in terms of assembly, making them accessible for non-specialist users. Conclusions: Three-dimensional printing offers an effective, low-cost alternative to traditional prosthetic manufacturing. However, variability in design, a lack of standardized manufacturing protocols, and limited clinical validation remain challenges. Future efforts should focus on establishing standardized guidelines, improving design consistency, and validating the clinical effectiveness of 3D-printed prostheses to ensure their long-term viability as functional alternatives to traditional devices.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".