Development of a wearable ultrasonic sensor and method for continuous monitoring of mechanical properties of plantar soft tissue for diabetic patients
Bibliographic record
Abstract
One of the long-term complications of diabetes is peripheral neuropathy, where insensitive nerves can lead to serious foot ulceration. Studies have shown that the mechanical properties of plantar soft tissues change with diabetes. Ultrasound methods could be used to measure plantar tissue thickness and mechanical properties, as a quantitative assessment tool. Diabetic shoes or orthoses are often custom-designed for each person to prevent foot injury during daily activities. This study developed an ultrasonic method and sensors that can be use between the foot and a custom insole to continuously monitor the mechanical properties of plantar soft tissue during physical activities. In the proposed sensor design, the protection layer on the sensing side (bottom electrode) was eliminated and the top side was electrically shielded to reduce environmental noises. A developed wearable ultrasonic sensor was used in a preliminary experiment to measure plantar tissue thickness. Plantar heel tissue thickness was successfully measured, decreasing from 16.2 mm to 10.1 mm with pressure changes from 0 to 190 kPa. Stress-strain pressure application and release curves and the heel tissue hysteresis parameter were also successfully calculated.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".