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Record W2907338308 · doi:10.1109/ifetc.2018.8583998

A Piezo Transducer Based Flexible Hybrid Sensor for Health Monitoring

2018· article· en· W2907338308 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
KeywordsTransducerSpirometerDiaphragm (acoustics)SIGNAL (programming language)Respiratory monitoringElectronicsComputer scienceMaterials scienceAcousticsElectronic engineeringElectrical engineeringRespiratory systemEngineeringVibrationMedicinePhysics

Abstract

fetched live from OpenAlex

Flexible hybrid electronics integrate both rigid electronics and printed materials on a flexible substrate. This integration results in high performance from thin, lightweight and flexible devices. In this paper, we propose a flexible hybrid sensor as part of a respiratory monitoring system. The sensor utilizes a PZT-4 ultrasound piezo transducer to track the motion of the diaphragm, diaphragmatic pleura and chest wall in order to find the respiratory cycles. Experimental results show that the respiratory signal obtained with the sensor matches very well with the respiratory signal monitored with an SPR-BTA spirometer.

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: none
Teacher disagreement score0.754
Threshold uncertainty score0.897

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 head0.028
GPT teacher head0.285
Teacher spread0.258 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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