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Record W2001960771 · doi:10.1109/iembs.2011.6090950

Validation of respiratory signal derived from suprasternal notch acceleration for sleep apnea detection

2011· article· en· W2001960771 on OpenAlexaff
Parastoo Dehkordi, M. Marzencki, Kouhyar Tavakolian, Marta Kamińska, Bożena Kamińska

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsMcGill University Health CentreSimon Fraser University
Fundersnot available
KeywordsAccelerometerSpirometrySIGNAL (programming language)AccelerationRespirationSleep apneaRespiratory systemObstructive sleep apneaApneaHypopneaSleep (system call)MedicineAnesthesiaComputer sciencePolysomnographyInternal medicinePhysicsAnatomyAsthma

Abstract

fetched live from OpenAlex

This study evaluates the respiration signal derived from an accelerometer mounted on the suprasternal notch in three body positions and three respiration types simulating normal sleep conditions. The Acceleration Derived Respiratory signal (ADR) is compared with single strain gauge belt and a standard spirometry signal taken as reference. The results demonstrate the potential of ADR as a simple, low cost and unintrusive method of screening breath disorders such as obstructive sleep apnea/hypopnea.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.290
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.078
GPT teacher head0.311
Teacher spread0.232 · 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

Citations28
Published2011
Admission routes1
Has abstractyes

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