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Record W2904235023 · doi:10.1109/icsict.2018.8565641

Design of a low electrode offset and high CMRR instrumentation amplifier for ECG acquisition systems

2018· article· en· W2904235023 on OpenAlexfundno aff
Jiwei Huang, Tai-Ming Huang, Fan-Yang Li

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAnalog and Mixed-Signal Circuit Design
Canadian institutionsnot available
FundersCanadian Food Inspection AgencyNational Science Foundation
KeywordsInstrumentation amplifierCommon-mode rejection ratioInput offset voltageElectronic engineeringElectrical engineeringOperational amplifierDC biasOperational transconductance amplifierOffset (computer science)AmplifierCMOSEngineeringComputer scienceVoltage

Abstract

fetched live from OpenAlex

A current feedback instrumentation amplifier (CFIA) for electrocardiogram (ECG) acquisition systems is proposed in this paper. In order to reduce the electrode offset (EOS) and baseline drift, an electrode offset cancellation module is used. Right leg drive (RLD) module is added to improve the common mode rejection ratio (CMRR), suppress common mode interference. An operational transconductance amplifier-capacitor (OTA-C) low-pass filter is integrated at the output of the CFIA to filter out high-frequency noise caused by the ambient environment. The circuit is designed and simulated using a 0.18 μm CMOS process. The circuit operates at 2V and consumes a total current of 47μA. Simulation results show that the CMRR of the circuit can reach 129dB, and the canceled electrode offset voltage is ±200mV.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.938
Threshold uncertainty score0.354

Codex and Gemma teacher scores by category

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

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 head0.013
GPT teacher head0.212
Teacher spread0.199 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations5
Published2018
Admission routes1
Has abstractyes

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