MétaCan
Menu
Back to cohort
Record W2101968900 · doi:10.1109/tbme.2005.844026

Automated Estimation of the Phase Between Thoracic and Abdominal Movement Signals

2005· article· en· W2101968900 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Biomedical Engineering · 2005
Typearticle
Languageen
FieldEngineering
TopicNon-Invasive Vital Sign Monitoring
Canadian institutionsMontreal Children's HospitalMcGill University
Fundersnot available
KeywordsComputer scienceBreathingPhase (matter)Artificial intelligence

Abstract

fetched live from OpenAlex

This paper presents a new procedure for the automated estimation of the phase relation between thoracic and abdominal breathing signals measured by inductance plethysmography (RIP). This estimation is achieved using linear filters, binary converters and an exclusive-or gate. The filters are designed offline from prior knowledge of the spectrum of subjects' respiration, reducing computational complexity and providing on-line processing capabilities. Some numerical results based on simulated time series and infant respiration data are provided, showing that the new method is less biased than the Pearson correlation method, commonly used for assessment of thoracoabdominal asynchrony. Our method offers further advantages: 1) it works with uncalibrated measurements; 2) it provides quantitative phase estimates with no need to estimate the underlying frequency of the breathing signals; 3) it does not require nonconvex optimization search algorithms; and 4) it is easy to implement and to automate.

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.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.673
Threshold uncertainty score0.600

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 head0.011
GPT teacher head0.265
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