An Ultraminiaturized Ultrawideband Low Profile Antenna for Skin, Muscle, and Heart Implantable Medical Devices
Bibliographic record
Abstract
We present an ultraminiaturized Ultrawideband low-profile antenna for wireless implantable medical communication systems (WIMCS). The radiating element of the miniaturized antenna is composed of Interconnected Concentric Square Loops (ICSLs) with a full ground plane. The proposed antenna has a small footprint of$6 \times 6 \times 0.71 ~\text{mm} 3$. The key to achieving the desired bandwidth is the interconnection between the feed point and the inner loop, and the interconnection between the inner and outer loops. Optimizing the location, length, and width of the interconnects yields miniaturization and wide bandwidth characteristics. The ICSL antenna operates in the ISM (0.902 GHz - 0.928 GHz), WMTS (1.395 GHz- 1.495 GHz), and Midfield band (1.45 GHz- 1.6 GHz) with a bandwidth of$>62 \%$over the 0.9 to 1.6 GHz frequency range. Initially, the wideband antenna was designed, optimized, and analyzed in a 3-layer phantom consisting of skin, fat, and muscle. A 4-layer phantom, consisting of skin, fat, muscle, and heart tissue, is designed to evaluate performance in heart tissue. The ultrawideband antenna exhibits omnidirectional radiation characteristics. The small footprint and ultrawideband bandwidth features make the proposed antenna a potential candidate for integration in WIMCS, such as skin implants, Arteriovenous Grafts (AVGs), and leadless pacemakers.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".