Fascicle-Selective Bidirectional Peripheral Nerve Interface IC with 173dB FOM Noise-Shaping SAR ADCs and 1.38pJ/b Frequency-Multiplying Current-Ripple Radio Transmitter
Bibliographic record
Abstract
The peripheral nervous system (PNS) provides a conduit through which organs can communicate with the central nervous system. PNS neural interfaces have been deployed in open-loop fashion to help restore motor or sensory functions in paralyzed or amputated individuals, and also as implantable closed-loop therapeutic devices for treating chronic medical conditions related to autoimmune or metabolic disorders. Their efficacy and the scope of clinical use, however, are severely curtailed by the invasiveness of the cable, electronics and battery, and the lack of nerve fascicle selectivity and online adaptivity. We present a battery-free wireless PNS interface that features a mm-scale fascicle-selective neural interface IC with extraneural recorders and stimulators, as well as a wearable interrogator with integrated machine learning (ML) to enable adaptive neuromodulation therapy with low invasiveness.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".