Design of Analog CMOS Circuits for Batteryless Implantable Telemetry Systems
Bibliographic record
Abstract
A wireless biomedical telemetry system is a device that collects biomedical signal measurements and transmits data through wireless RF communication. Testing medical treatments often involves experimentation on small laboratory animals, such as genetically modified mice and rats. Using batteries as a power source results in many practical issues, such as increased size of the implant and limited operating lifetime. Wireless power harvesting for implantable biomedical devices removes the need for batteries integrated into the implant. This will reduce device size and remove the need for surgical replacement due to battery depletion. Resonant inductive coupling achieves wireless power transfer in a manner modelled by a step down transformer. With this methodology, power harvesting for an implantable device is realized with the use of a large primary coil external to the subject, and a smaller secondary coil integrated into the implant. The signal received from the secondary coil must be regulated to provide a stable direct current (DC) power supply, which will be used to power the electronics in the implantable device. The focus of this work is on development of an electronic front-end for wireless powering of an implantable biomedical device. The energy harvesting front-end circuit is comprised of a rectifier, LDO regulator, and a temperature insensitive voltage reference. Physical design of the front-end circuit is developed in 0.13um CMOS technology with careful attention to analog layout issues. Post-layout simulation results are presented for each sub-block as well as the full front-end structure. The LDO regulator operates with supply voltages in the range of 1V to 1.5V with quiescent current of 10.5uA The complete power receiver front-end has a power conversion efficiency of up to 29%.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".