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An Active Electrode IC with Embedded Analog CMRR Enhancement for Interference- and Gain-Mismatch-Resilient EEG Recording

2021· article· en· W4200156269 on OpenAlexaff
Alireza Dabbaghian, Hossein Kassiri

Bibliographic record

Venue2021 IEEE Biomedical Circuits and Systems Conference (BioCAS) · 2021
Typearticle
Languageen
FieldEngineering
TopicAnalog and Mixed-Signal Circuit Design
Canadian institutionsYork University
Fundersnot available
KeywordsCommon-mode rejection ratioCMOSElectronic engineeringComputer scienceMaterials scienceElectrical impedanceElectrical engineeringAmplifierEngineeringOperational amplifier

Abstract

fetched live from OpenAlex

We report the design, implementation, and experimental characterization of an EEG recording active electrode (AE) architecture that features analog in-AE common-mode rejection ratio (CMRR) improvement. Detailed system-level architecture and circuit implementation of the proposed AE is presented following a brief analytical and comparative review of the effect of gain and electrode impedance mismatch on CMRR degradation in state-of-the-art AE-based wearable EEG recording systems. An active electrode integrated circuit (IC) based on the proposed CMRR-enhancing architecture is fabricated in a 180nm CMOS technology and is experimentally characterized. Our measurement results show a CMRR of 82.2dB (at 60Hz), amplification voltage gain of 52.8dB, a bandwidth of 0.2-400Hz, ±350mv input DC offset tolerance, and 0.66µv integrated input referred noise (0.5-100Hz), while consuming 13.5µW per channel. An EEG recording has been performed using the developed AE IC connected to active electrodes placed on the forehead.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.705
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.025
GPT teacher head0.245
Teacher spread0.220 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

Explore more

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