Safety-Optimized Inductive Powering of Implantable Medical Devices: Tutorial and Comprehensive Design Guide
Bibliographic record
Abstract
A tutorial and comprehensive guide are presented for the design of planar spiral inductors with maximum energy delivery in biomedical implants. Rather than maximizing power transfer efficiency (PTE), the ratio of the received power to the square of the magnetic flux density is maximized in this technique. This ensures that the highest power is delivered for a given level of safe electromagnetic radiation, as measured by the specific absorption rate (SAR) in the tissue. By using quasi-static field approximations, the maximum deliverable power under SAR constraints is embedded in a lumped-element model of a 2-coil inductive link, from which planar coil geometries are derived. To compare the proposed methodology with the conventional approach that maximizes PTE, the results of both techniques are compared for three examples of state-of-the-art designs. It is demonstrated that the presented technique increases the maximum deliverable power while operating at a given level of non-ionizing radiation by factors of 8×, 410×, and 560× as compared to the three existing designs, and maintaining moderate link efficiencies of 12%, 23%, and 12%, respectively.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.013 |
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".