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Record W4220936783 · doi:10.1117/12.2628583

The development of wearable ECG device

2022· article· en· W4220936783 on OpenAlexaff
Yuxi Guo, Shuyi Ran, Sheng Wang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicECG Monitoring and Analysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsWearable computerSmartwatchComputer scienceWearable technologySoftwareComputer hardwareEmbedded systemProcess (computing)Body area networkData acquisitionWirelessTelecommunications

Abstract

fetched live from OpenAlex

With the progress of telecommunication technology, remote acquisition and data analysis have become possible. Electrocardiogram (ECG) is the measure of the electrochromic activity of the heart and is an important human body data. Therefore, portable continuous ECG acquisition is an important part of family health care, which can be realized by wearable devices such as smartwatches. This paper aims to review the development of wearable ECG devices from aspects of hardware and software design. In the hardware part, this paper focuses on the design of electrodes that directly receive signals from the human body and the integrated circuit inside the wearable devices. The extraction, process and transmission of the obtained ECG signal are discussed in the software part. This article can provide a reference for those who are interested in understanding wearable ECG technologies or designing new wearable devices.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.824
Threshold uncertainty score0.334

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 head0.026
GPT teacher head0.288
Teacher spread0.262 · 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 designNot applicable
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

Citations0
Published2022
Admission routes1
Has abstractyes

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