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Continuous Artery Wall Motion Tracking Using Flexible and Wearable Ultrasonic Sensor by Signal Decomposition

2021· article· en· W3177749008 on OpenAlexaff
Shane Steinberg, Yuu Ono, Sreeraman Rajan, Shanmugaraja Krishnasamy Venugopal

Bibliographic record

Venue2021 IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS) · 2021
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Disease Prevention
Canadian institutionsCarleton University
Fundersnot available
KeywordsUltrasonic sensorSIGNAL (programming language)AcousticsWaveformEcho (communications protocol)UltrasoundWearable computerTracking (education)Materials scienceComputer sciencePhysicsTelecommunications

Abstract

fetched live from OpenAlex

A flexible and wearable ultrasonic sensor (WUS) constructed from a piezoelectric polymer film has been proposed for long-term continuous monitoring of the artery motion. The non-focused plane-wave ultrasonic beam of the WUS requires a signal processing methodology that can isolate the arterial wall echo from undesired scattering echoes caused by the adjacent tissues. Matching pursuit signal decomposition based on the Gaussian modulated sinusoidal signal model was performed to isolate the wall echo. Using the parameters of the isolated wall echo, the wall motion was estimated over the ultrasound signals acquired in M-mode. The result captured the artery wall motion associated with the blood pressure waveform.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.714
Threshold uncertainty score0.991

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 head0.052
GPT teacher head0.326
Teacher spread0.274 · 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
Published2021
Admission routes1
Has abstractyes

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