Multidisciplinary co-creation, design and clinical evaluation of a two-material 3D printed ankle-foot orthosis: Preliminary clinical findings in a case report of fibular hemimelia
Bibliographic record
Abstract
Lower-limb orthoses are often either standardized, lacking personalization for individual clinical needs, or custom-made, which is time-consuming and labor-intensive for orthotists. To address this gap, this study proposes a co-creation methodology for developing a customized orthosis, integrating 3D scanning, computer-aided design (CAD), and 3D printing with feedback from both the clinical team and the patient's caregivers. The methodology was applied to a fibular hemimelia case study, where the orthosis was designed based on 3D scans and printed using two materials: thermoplastic polyurethane (TPU) for flexibility and polyethylene terephthalate glycol (PETG) for rigidity. Usability and satisfaction assessments were conducted using the System Usability Scale (SUS) and the Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST 2.0). The orthosis met the clinical requirements, allowing the child to take a normal stride without discomfort (SUS: 92.5/100; QUEST 2.0: 4.2/5). Although the orthosis fractured at the ankle after a few hours of use, the study provided crucial insights for future design improvements. These findings highlight the utility of this co-creation approach in developing personalized orthotic models and demonstrate the advantages of using multi-material 3D printing to enhance orthosis functionality.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".