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Record W2116236092 · doi:10.1109/iembs.2009.5334008

Pulse transit time-based blood pressure estimation using hilbert-huang transform

2009· review· en· W2116236092 on OpenAlexaff
Qiao Zhang, Yang Shi, D. Teng, Anh Dinh, Seok‐Bum Ko, Li Chen, Jenny Basran, Vanina Dal Bello‐Haas, Younhee Choi

Bibliographic record

Venuenot available
Typereview
Languageen
FieldEngineering
TopicNon-Invasive Vital Sign Monitoring
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsBlood pressurePulse (music)Pulse waveComputer sciencePulse pressureTransit timeHilbert transformMathematicsMedicineEngineeringTelecommunicationsInternal medicineTransport engineering

Abstract

fetched live from OpenAlex

The pulse transit time (PTT) based method has been suggested as a continuous, cuffless and non-invasive approach to estimate blood pressure. It is of paramount importance to accurately determine the pulse transit time from the measured electrocardiogram (ECG) and photoplethysmo-gram (PPG) signals. We apply the celebrated Hilbert-Huang Transform (HHT) to process both the ECG and PPG signals, and improve the accuracy of the PTT estimation. Further, the blood pressure variation is obtained by using a well-established formula reflecting the relationship between the blood pressure and the estimated PTT. Simulation results are provided to illustrate the effectiveness of the proposed method.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.025
GPT teacher head0.267
Teacher spread0.242 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations17
Published2009
Admission routes1
Has abstractyes

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Same topicNon-Invasive Vital Sign MonitoringFrench-language works237,207