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Record W1993523857 · doi:10.1109/biocas.2011.6107808

An 8-channel readout front-end for long-term sleep quality monitoring

2011· article· en· W1993523857 on OpenAlexfundno aff
Xiaofei Pu, Hui Zhang, Yajie Qin, Zhiliang Hong

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAnalog and Mixed-Signal Circuit Design
Canadian institutionsnot available
FundersCanadian Food Inspection Agency
KeywordsCMOSFront and back endsNoise (video)AmplifierInstrumentation amplifierAnalog front-endComputer scienceChannel (broadcasting)Electrical engineeringChipFilter (signal processing)Common-mode rejection ratioTerm (time)Computer hardwareElectronic engineeringEngineeringOperational amplifierPhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

An 8-channel readout front-end (RFE) for long-term sleep quality monitoring is presented in this paper and features high common-mode rejection ratio (CMRR) and low input referred noise. Each channel is composed of an AC coupled instrumentation amplifier (IA) with chopping spike filter (CSF), a programmable gain amplifier (PGA), and a buffer, while the bias generator and non-overlapping clock are shared by all channels. The proposed circuit, built in standard 0.35 μ m CMOS technology, consumes 101 μ A from 2.7 V, while occupying 5 mm2of chip area. According to the simulation, the AC coupled IA's CMRR is 118 dB and input referred noise is merely 0.55 μ Vrms. Meanwhile, the RFE is digitally programmable for different applications.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.086
GPT teacher head0.288
Teacher spread0.202 · 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 source (direct Gemma or distilled Codex), 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

Citations11
Published2011
Admission routes1
Has abstractyes

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