Polarization Reconfigurable Planar Inverted-F Antenna for Implantable Telemetry Applications
Bibliographic record
Abstract
A polarization reconfigurable implantable planar inverted-F antenna (PIFA), operating at 2.45–GHz ISM band, is introduced for monitoring and biotelemetry purposes. The proposed implantable antenna featuring with the reconfigurability of two polarizations is effective to overcome the polarization mismatch and multi-path reflection in an indoor environment. By using two groups of PIN diodes as radio frequency (RF) switches along$x$-direction and$y$-direction respectively, two orthogonal linear polarizations can be switched to avoid communication link failure. The proposed antenna is based on a planar inverted-F antenna structure and the implantable environment of human body to develop. The antenna exhibits a good stability of an impedance bandwidth with the reflection coefficient ≤−10 dB in the environment of a human phantom. The simulated results in simple muscle-layer phantom, multi-layer phantom and 3D realistic human voxel model demonstrates the good robustness of the proposed antenna in the complex implantable environment. An in-vitro test was carried out in body tissue simulant liquid to validate our proposed design. A sleeve balun was fabricated and incorporated into the semirigid coax cable in order to eliminate the unwanted effect of the long cable during the measurement. The experimental results agree with simulation and show an overlapped impedance bandwidth of 9.1% from 2.3 GHz to 2.52 GHz in different reconfigurable states. The radiation performances, evaluation of Specific Absorption Rate (SAR), and link characteristics in different propagation scenarios are also discussed. This proposed antenna technology is suitable for implantable telemetry applications.
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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) | 0.001 | 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".