Kirigami Integrated Yagi-Uda Antenna for Strain Sensing in Biomedical Applications
Bibliographic record
Abstract
This paper presents a low-profile flexible microstrip Yagi- Uda array antenna with strain sensing capability assisted by a Kirigami structure and design. The Yagi-Uda array was integrated on a PET substrate with a thickness of$100\mu{\mathrm{m}}$, demonstrating strain-induced changes in the antenna's resonant frequency and impedance bandwidth. Operating based on the concept of mutual impedance, displacing the director elements of the antenna by an applied force (i.e., strain), affects the mutual coupling of array elements, and consequently impacts the antenna parameters. The unstrained antenna operated at 5.32 GHz, showing a 1.7% fractional bandwidth with a measured estimated gain of 5.86 dBi. For variations in the range of 3–7 cm from the initial length, equivalent to 27-63% strain, the observed shift in the resonant frequency was$140\sim 4$MHz, respectively. This antenna array with both communication and strain-sensing capabilities is a proof of concept for multi-functional, wearable/flexible microwave devices in biomedical applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.001 |
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".