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Record W2888067344 · doi:10.1115/1.4041190

A Sensor System to Measure Force Applications of a Brace for Pectus carinatum

2018· article· en· W2888067344 on OpenAlexafffund
Tomasz Bugajski, Douglas Kondro, Kartikeya Murari, Janet L. Ronsky

Bibliographic record

VenueJournal of Medical Devices · 2018
Typearticle
Languageen
FieldMedicine
TopicPectus Deformity Diagnosis and Treatment
Canadian institutionsUniversity of Calgary
FundersMitacs
KeywordsPectus carinatumBraceCalibrationMeasure (data warehouse)Limits of agreementCompression (physics)SimulationReliability (semiconductor)Biomedical engineeringComputer scienceSurgeryStructural engineeringEngineeringMedicineMathematicsPhysicsStatisticsPower (physics)Pectus excavatumNuclear medicine

Abstract

fetched live from OpenAlex

Pectus carinatum (PC) presents itself as a protrusion on the chest wall of adolescent individuals. Current treatment for PC is performed with a Pectus carinatum orthosis (PCO) that applies a compressive force to the protrusion. While this treatment is accepted, the magnitude of compressive forces applied remains unknown leading to excessive or deficient compression. Although the need for this quantitative data is recognized, no studies reporting the data or methods are available. The purpose of this study was to design an accurate force measurement system (FMS) that could be incorporated into a PCO with minimal bulk. Components of the FMS were three-dimensional (3D)-printed and incorporated into an existing PCO design. The FMS was calibrated using a custom indenter that applied forces to the FMS in a controlled manner. Evaluation of the FMS on five human participants was also performed. A reliability measure of the FMS was calculated for analysis. The FMS was implemented into the PCO and able to withstand the applied forces. The calibration revealed an increase in load cell error with increased magnitude of applied force (mean error [SD] = 5.59 N [6.48 N]). Participants recruited to evaluate the FMS demonstrated reliable forces (R = 96%) with smaller standard deviations than those during the calibration. The FMS was shown capable of measuring PCO forces but requires further testing and improvement. This system is the foundational component in a wireless, minimalistic sensor system to provide real time force feedback to both the clinician and patient.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.673
Threshold uncertainty score0.269

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.020
GPT teacher head0.325
Teacher spread0.305 · 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 designNot applicable
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

Citations2
Published2018
Admission routes2
Has abstractyes

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