Toward A Fully Integrated Neurostimulator With Inductive Power Recovery Front-End
Why this work is in the frame
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Bibliographic record
Abstract
In order to investigate new neurostimulation strategies for micturition recovery in spinal cord injured patients, custom implantable stimulators are required to carry-on chronic animal experiments. However, higher integration of the neurostimulator becomes increasingly necessary for miniaturization purposes, power consumption reduction, and for increasing the number of stimulation channels. As a first step towards total integration, we present in this paper the design of a highly-integrated neurostimulator that can be assembled on a 21-mm diameter printed circuit board. The prototype is based on three custom integrated circuits fabricated in High-Voltage (HV) CMOS technology, and a low-power small-scale commercially available FPGA. Using a step-down approach where the inductive voltage is left free up to 20 V, the inductive power and data recovery front-end is fully integrated. In particular, the front-end includes a bridge rectifier, a 20-V voltage limiter, an adjustable series regulator (5 to 12 V), a switched-capacitor step-down DC/DC converter (1:3, 1:2, or 2:3 ratio), as well as data recovery. Measurements show that the DC/DC converter achieves more than 86% power efficiency while providing around 3.9-V from a 12-V input at 1-mA load, 1:3 conversion ratio, and 50-kHz switching frequency. With such efficiency, the proposed step-down inductive power recovery topology is more advantageous than its conventional step-up counterpart. Experimental results confirm good overall functionality of the system.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 it