Novel Pressure-Sensing Smart Insole System Used for the Prevention of Pressure Ulceration in the Insensate Foot
Bibliographic record
Abstract
Wounds of the foot challenge reconstructive surgeons to manage multiple factors: sensibility, stability, and durability. In this article, we focus on the insensate foot, which poses challenges to wound prevention with its propensity to develop pressure ulceration. The authors present the innovative use of a pressure-sensing smart insole system (SurroSense Rx, Orpyx Medical Technologies Inc., Calgary, Canada) in the management of the insensate foot in a patient following foot reconstruction. The pressure-sensing smart insole system provided unique feedback to both patient and provider in ways that contributed to the prevention of pressure ulcer recurrence, as well as highlight the importance of prescribed footwear in both the affected and unaffected foot. Wearable real-time monitoring and feedback faces the challenge of patient adherence. Future studies are indicated to examine the specific behaviors that are associated with favorable outcomes and long-term behavior changes.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".