Low power noise immune circuit for implantable CMOS neurochemical sensor applied in neural prosthetics
Bibliographic record
Abstract
In this manuscript, we present the features and describe the operation of a low power, noise immune circuit for a CMOS based neurochemical sensor for implantable neural prosthetics. This microsystem consists of a single ended low noise low power amplifier and an integrator, in addition to a 10-bit first order sigma delta Analog to Digital Converter (ADC). Using electrochemical techniques, it senses picoscale to microscale current which corresponds to micro molar neurotransmitter concentration and converts the measurement to a 10-bit digital code. Combining amperometry and fast-scan cyclic voltammetry electrochemical technique results in a sensor with a high selectivity while having elevated temporal resolution. The microsystem consumes 120.85 μW which is the lowest reported brain implant and biosensor power consumption. This circuit is designed in CMOS 0.18 μm technology. Integration is an averaging operation and provides significant noise immunity. The low noise characteristics of our design make this device suitable for the noisy environment often encountered in-vivo.
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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) | 0.000 | 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 | 0.001 |
| 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".