Biomimetic Orthopedic Footwear Advanced Insole Materials to Be Used in Medical Casts for Weight-Bearing Monitoring
Bibliographic record
Abstract
Fabrication, characterization and testing of protective biomimetic orthopedic footwear advanced insole materials are introduced. The main objective of this material is to preserve and isolate a set of sensors for the Weight-Bearing Monitoring System (WBMS) device. Twenty-one samples of renewably sourced Polyurethane Foam (PUF) composed of poly(trimethylene ether) glycol (PO3G) and unmodified castor oil (CO) were synthesized and evaluated according to predetermined criteria. Response surface methodology of Box—Behnken design was applied to study the effect of the polyols ratio, isocyanate index (II), and blowing agent ratio on the properties (hardness, density) of PUFs. Results showed that CO/PO3G/Tolyene Diisocyanate (TDI) PUFs with hardness Shore A 17–22 and density of 0.19–0.25 g/cm3 demonstrate the required characteristics and can potentially be used as a durable and functional insole material. Phase separation studies have found the presence of well-segregated structures in PUFs having polyols ratio of CO:PO3G 1:3 and low II, which further explains their extraordinary elastic properties (400% elongation). Analysis of cushioning performance of PUF signified that five samples have Cushioning Energy (CE) higher than 70 N·mm and Cushioning Factor (CF) in the range of 4–8, hence are recommended for application in WBMS due to superior weight-bearing and pressure-distributing properties. Moreover, the developed formulation undergoes anaerobic soil bacterial degradation and can be categorized as a “green” bio-based material.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".