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Record W3162491331 · doi:10.1002/tee.23388

Bioimpedance‐based plethysmogram detection using MHz band

2021· article· en· W3162491331 on OpenAlexfundno aff
Dairoku Muramatsu

Bibliographic record

VenueIEEJ Transactions on Electrical and Electronic Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicNon-Invasive Vital Sign Monitoring
Canadian institutionsnot available
FundersDavid Suzuki Foundation
KeywordsWearable computerPlethysmographAcousticsElectrical impedanceComputer scienceBiomedical engineeringElectrical engineeringElectronic engineeringPhysicsEngineeringMedicineCardiologyEmbedded system

Abstract

fetched live from OpenAlex

Daily pulsation measurements are useful for managing various health conditions. In this article, we discuss the development of a technique that uses wearable devices for measuring pulsations using bioimpedance. The pulsations from the study subject were measured using wrist‐attached electrodes in the MHz band. Results showed that pulsations can be measured based on the changes in the bioimpedance under all studied conditions. Moreover, the bioimpedance changed with the pulsations even in discontinuous measurements. These results show the feasibility of bioimpedance‐based plethysmogram detection using the MHz band. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

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 score0.707
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.203
Teacher spread0.195 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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