Simultaneous Wireless Powering and Biotelemetry for Biomedical Implants Using 3-D Printable Water-Based Self-Diplexing Antennas
Bibliographic record
Abstract
This article presents water-based (WB) single-input single-output (SISO) and multiple-input multiple-output (MIMO) self-diplexing antennas designed for implantable devices. The SISO WB self-diplexing (WBSD) antenna is designed with two elements of different heights: the element with a height of 7 mm resonates at 1.45 GHz for wireless power transfer (WPT), and the other with a height of 4.2 mm resonates at 2.45 GHz for bio-telemetry. To convert the SISO into an MIMO, the circular radiators are repositioned toward the boundary and mirrored to the opposite boundary of the antenna. The operating frequencies of both versions can be customized by adjusting their heights and radii. These SISO and MIMO self-diplexers are considered safer for users as they use water and metal without any slots. To create an efficient system capable of both biotelemetry and battery recharging, the WBSD antenna prototypes are connected to a full-wave rectifier inside a capsule device, and different tests are performed. The efficiency of the WPT is improved by about 30% using the spatial power combining (SPC) techniques. Both the SISO and MIMO self-diplexers can be produced using a 3-D printer and copper tapes, resulting in lower production costs.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".