Electro-mechanical properties of knitted wearable sensors: Part 2 – Parametric study and experimental verification
Bibliographic record
Abstract
An optimization design simulating the electro-mechanical property of the conductive elastic knitted fabric is built based on a loops structure under biaxial extensions. A computer program can give the fabric equivalent resistance, which is obtained by solving the circuit network equations. So, it can simplify the computational process immensely. In order to simplify the calculation of the contacting forces on the overlapped yarns, two hooked yarns are used to represent the loop configurations. From the theoretical analysis and experimental investigations, it is found that the resistance changing due to the yarn segment transfer is the key factor for the sensitivity of elastic fabric sensors. This makes the resistance linear increasing with the strain increasing. Analysis of the experimental results show that change in the resistance of a fabric sensor due to the contact resistance has a minor contribution to the sensitivity of the sensor in the large-strain regime. Also, the fabric structure and the yarn elongating affect the characteristics of the fabric sensor.
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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 | 0.001 |
| 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 | 0.001 |
| 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".