Fully implantable, multi‐channel microstimulator with tracking supply ribbon, multi‐output charge pump and energy recovery
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract A novel energy‐efficient approach dedicated to high‐density implantable stimulators such as visual prostheses is presented. Energy efficiency of the approach proposed in this work is achieved through two ideas: the ‘tracking supply ribbon’ technique and ‘reverse charge pumping’. The proposed approach is implemented, in the multi‐channel case, in such a way that power efficiency of each stimulation channel is enhanced according to its specific voltage/current condition and independently from other channels. For this purpose, a multi‐channel power‐efficient charge pump circuit with small integrated capacitors is proposed. Based on the proposed approach, a fully integrated 16‐channel stimulation backend for a visual prosthesis was designed and simulated in the transistor level in a standard 0.18‐μm triple‐well CMOS technology, occupying 1.41 mm 2 of silicon area. According to post‐layout simulation results, power savings of up to 74% for a single channel and 81.5% for multiple channels are achieved compared to the conventional output stage with a constant supply voltage. Designed for the proposed stimulation backend, the charge pump generates output voltages of 3.48 V, −1.69 V, −3.38 V, and −5.05 V out of a 1.8 V input voltage and exhibits average power efficiency of 92.8% and 86.8% for one‐ and three‐stage circuits, respectively, all in the case of a 100 μA current load. All the aforementioned results are based on post‐layout simulation. Moreover, a proof‐of‐concept prototype was developed using off‐the‐shelf components in order to demonstrate the operation of the proposed tracking supply ribbon idea.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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