Biomechanical Efficacy of Shear-Reducing Diabetic Insoles: Elaborations on Future Design Criteria
Bibliographic record
Abstract
ABSTRACT Introduction Increasing evidence suggests that plantar shear forces and related stresses play a major role in diabetic foot ulcerations. Several orthotic devices are commercially available to reduce plantar shear forces within the shoe. The biomechanical efficacy of these devices was not tested in vivo. To measure spatiotemporal characteristics of gait to assess the efficacy of such shear-reducing insoles (SRIs), control insoles were also tested for comparison purposes. Material and Methods Eighteen healthy volunteers walked along a 30.5-m line while wearing three types of insoles in randomized order. Spatiotemporal parameters of gait were quantified. Statistical comparisons between the control and SRIs were conducted using repeated measures analysis of variance. Intraclass correlation coefficients (ICCs) were also calculated to reveal the repeatability of the trials. Step length, gait speed, and cadence of the subjects remained similar regardless of the insole type. Results No significant difference was observed in any variable. The ICC values revealed excellent repeatability. Conclusions The lack of changes in gait parameters in these results suggest that shear-reducing diabetic inserts did not decrease plantar shear forces as intended. This might be caused by unrealistic in vitro testing conditions during the prototype development. Future designs should also consider friction at the lateral walls of the inserts, an increase in step repetition that accompanies a decrease in gait speed and/or step length, and a possible temperature increase within the shoe. We conclude that the future SRIs need to be redesigned based on comprehensive biomechanical guidelines.
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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 | 0.021 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".