AN IMPLANT FOR A VISUAL CORTICAL STIMULATOR
Bibliographic record
Abstract
We present the design of an implantable micro-stimulator intended for a cortical visual prosthesis. The device is composed of several integrated modules to be assembled on a thin and flexible substrate providing placement flexibility on the cortex. The stimulator provides the user with significant usage flexibility, supplying biphasic current pulses using either monopolar or bipolar configurations, with single or distributed return electrode, and having a fixed or dynamic reference voltage. Monitoring of electrode-tissue interface condition is possible by measuring both simulation currents and voltages at any electrode for enhanced safety, and for enabling troubleshooting after implantation. In order to avoid erroneous stimulation to be executed, potentially caused by the implant's wireless transcutaneous power transfer, constant parameters stored in volatile memory are constantly monitored, and in case of data corruption, stimulation is automatically disabled. A power efficient recovery and regulation circuit is proposed for providing dual supply voltages. Also, a bidirectional wireless link with data rates up to 1.5 Mbps and 500 kbps, downlink and uplink respectively, has been designed for use with a 13.56 MHz carrier. Performances attained with a prototype, combined with the stimulator module's configurable communication protocol, are suitable for a cortical implant having more than 1000 stimulation sites, which is expected to be sufficient for providing blind subjects with a useful vision.
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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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".