MétaCan
Menu
Back to cohort
Record W2907818895 · doi:10.1109/icsens.2018.8589856

Ultrasound Based Respiratory Monitoring Evaluation Under Human Body Motions

2018· article· en· W2907818895 on OpenAlexaff
Amirhossein Shahshahani, Sharmistha Bhadra, Željko Žilić

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicNon-Invasive Vital Sign Monitoring
Canadian institutionsMcGill University
Fundersnot available
KeywordsSpirometerPhotoplethysmogramDiaphragm (acoustics)UltrasoundComputer scienceRobustness (evolution)Biomedical engineeringDiaphragmatic breathingMatch movingBreathingRemote patient monitoringAcousticsComputer visionVibrationMotion (physics)EngineeringMedicineRadiologyAnatomySurgeryPhysics

Abstract

fetched live from OpenAlex

A novel pulmonary monitoring system based on diaphragm wall motion tracking is proposed. Diaphragm motions are measured by a designed ultrasound sensory system with only one ultrasound PZT5 piezo transducer. We evaluate the accuracy and robustness of this technique in monitoring the diaphragmatic function and its contribution to respiratory workload. The ultrasound sensor is placed in the zone of apposition (ZOA). Measurements are referenced to a SPR-BTA commercial spirometer. In this study, we also evaluate inertial and photoplethysmography (PPG) sensors as two alternative methods in this area. All tests are done in non-stationary human body situation to evaluate the usage of sensors in a real life. According to the diaphragm motion tracking of the proposed method, the system is extremely insensitive to motion artifacts. Promising results were obtained for the proposed system from four different tests with an average sensitivity and specificity of 88% and 73.5% in respiration detection, respectively.

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 categoriesnone
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 score0.076
Threshold uncertainty score0.775

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 head0.053
GPT teacher head0.311
Teacher spread0.257 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2018
Admission routes1
Has abstractyes

Explore more

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