Fully Inkjet-Printed Soft Wearable Strain Sensors Based on Metal/Polymer Composite Sensing Films
Bibliographic record
Abstract
In this paper, we present a high-performance soft strain sensor that uses composite sensing layers made of metal and polymer. This strain sensor is entirely developed by inkjet-printing the composite films on a highly stretchable thermoplastic polyurethane (TPU) substrate and a textile-compatible polymer film, which makes the process easy, affordable, energy-efficient, and scalable. The sensing patches are made up of two films: a PEDOT:PSS-based conductive polymer top film and a metal bottom film composed of silver nanoparticles. The sensor has a decent sensing range (≈10% strain), high sensitivity (GF ≈ 12), and outstanding mechanical stability (>1000 cycles), making it suitable for both stretching and bending deformation detection. As application examples, the soft sensors are used to track the highly deformed human body motions, displaying excellent performance. The outcomes demonstrate the attractiveness and potential of our low-cost soft strain sensors for real-world uses, such as the wide-range tracking of human movements.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".