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Record W2477175099 · doi:10.1109/jssc.2016.2582863

A 2.89 μW Dry-Electrode Enabled Clockless Wireless ECG SoC for Wearable Applications

2016· article· en· W2477175099 on OpenAlexaff
Xiaoyang Zhang, Zhe Zhang, Yongfu Li, Changrong Liu, Yong‐Xin Guo, Yong Lian

Bibliographic record

VenueIEEE Journal of Solid-State Circuits · 2016
Typearticle
Languageen
FieldEngineering
TopicAnalog and Mixed-Signal Circuit Design
Canadian institutionsYork University
FundersNational Research Foundation Singapore
KeywordsComputer scienceAsynchronous communicationCMOSChipWirelessElectronic engineeringEmbedded systemEngineeringComputer hardwareTelecommunications

Abstract

fetched live from OpenAlex

This paper presents a fully integrated wireless electrocardiogram (ECG) SoC implemented in asynchronous architecture, which does not require system clock as well as off-chip antenna. Several low power techniques are proposed to minimize power consumption. At the system level, a newly introduced event-driven system architecture facilitates the asynchronous implementation, thus removes the system clock leading to a true ECG-on-chip solution. A DC-coupled analog front-end is introduced together with a baseline stabilizer to boost the input impedance to 3.6 GQ and mitigate the electrode offset, which is less sensitive to motion artefact and contact impedance imbalance, making it well suited for dry-electrode based applications. Level-crossing analog-to-digital converter (LC-ADC) is employed to take the advantage of burst nature of ECG signal leading to at least 5 times reduction in sampling points compared to Nyquist sampling. A digitally implemented impulse-radio ultra-wideband transmitter is seamlessly integrated with LC-ADC and an on-chip antenna for wireless communications. Implemented in 0.13 μm CMOS technology, the ECG-on-chip consumes 2.89 μW under 1.2 V supply while transmitting the raw ECG data, which attains one order of magnitude lower than the current state-of-the-art designs. The fully integrated ECG SoC requires no external clocks and off-chip antenna, making it a good candidate for low cost and disposable wireless ECG patches, such as epidermal electronics.

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)0.000
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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.002

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 head0.015
GPT teacher head0.240
Teacher spread0.225 · 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

Citations76
Published2016
Admission routes1
Has abstractyes

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