Circularly Polarized Dual-Mode Wearable Implant Repeater Antenna With Enhanced Into-Body Gain
Bibliographic record
Abstract
A wearable stripline-fed circularly polarized dual-patch antenna structure that exhibits enhanced into-body gain is presented. The antenna is designed for body-surface repeater solutions and it addresses the problem of marginal into-body deep tissue communication links, where power consumption is of the utmost importance and system link efficiency is critical. Under realistic operation conditions, the antenna's circular polarization (CP) successfully mitigates implant orientation and polarization mismatch. Polarization loss for linear antennas can be up to 16 dB in anechoic environments and as much as 12.5 dB in a realistic multipath environment, as demonstrated by measured co- and cross-polar forward path gain between implanted and linearly polarized surface antennas. To overcome the body-isolating effect of an antenna ground plane and to produce an effective off-body mode, a novel dual-aperture stripline feed was developed which also improves the body-mounted antenna radiation efficiency. The antenna provides a 0 dBi off-body gain while still maintaining excellent into-body performance. The into-body link was shown to exhibit CP with a maximum isolation of only 1.5 dB between co- and cross-polar measurements in the 2.36-2.4 GHz band. All measurements were carried out using an accurate, next-generation layered phantom tested representative of a wide range of the population.
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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 | 0.001 | 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".