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Record W2110280116

Seismocardiograms return valid heart rate variability indices

2013· article· en· W2110280116 on OpenAlexaff
Alexandre Laurin, Andrew P. Blaber, Kouhyar Tavakolian

Bibliographic record

VenueComputing in Cardiology Conference · 2013
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsUniversity of British ColumbiaSimon Fraser University
Fundersnot available
KeywordsHeart rate variabilityOrthostatic vital signsElectrocardiographyHeart rateCardiologyBlood pressureMedicineInternal medicineMathematicsStatistics
DOInot available

Abstract

fetched live from OpenAlex

HRV indices have traditionally been acquired using interbeat intervals obtained from the electrocardiogram (ECG) R-wave. Preliminary studies have recently shown, however, that interbeat intervals obtained from seismocardiogram (SCG) isovolumic moment point return some valid HRV measurements. This presents an interesting discovery due to the recent ubiquity of affordable accelerometers of satisfactory sensitivity in mobile phones. For this purpose an orthostatic stress test of graded lower body negative pressure (LBNP) was used to compare HR V indices obtained from ECG and SCG during periods of different orthostatic stress. We conclude that estimates of interbeat intervals obtained using SCG markers are valid measurements of interbeat interval when compared with ECG and lend themselves validly to time-domain and frequency-domain HRV analysis. It is our recommendation that aortic opening SCG markers be used to obtain interbeat intervals as they represent well defined events and are obtainable without the use of ECG markers.

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)0.002
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.030
GPT teacher head0.284
Teacher spread0.254 · 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 designObservational
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

Citations34
Published2013
Admission routes1
Has abstractyes

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