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Record W1955153168 · doi:10.1109/icecs.2000.913024

Low-power CMOS implantable nerve signal analog processing circuit

2002· article· en· W1955153168 on OpenAlexaff
Adnan Harb, Mohamad Sawan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsCMOSElectrical engineeringSwitched capacitorAnalog signal processingOperational amplifierElectronic engineeringInstrumentation amplifierAmplifierCapacitorComputer scienceEngineeringAnalog signalVoltageDigital signal processing

Abstract

fetched live from OpenAlex

We describe a low-voltage low-power CMOS nerve signal analog processing circuit for biomedical applications. It is dedicated to an implantable bladder controller. After amplifying the nerve signal with low-noise high-CMRR instrumentation amplifier, it is rectified and bin-integrated (RBI) with a low-power CMOS analog processing circuit. This circuit is based on switched capacitor technique. Using techniques to reduce operational amplifier requirements ensures low-power consumption. The circuit has been designed in CMOS 0.35 /spl mu/m technology. The simulation results of the main parts of the proposed analog circuit are presented. At a supply voltage of 2.2 V the power dissipation is 700 /spl mu/W.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.048
GPT teacher head0.239
Teacher spread0.191 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2002
Admission routes1
Has abstractyes

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