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Record W2108442930 · doi:10.1109/tbme.2007.912640

A New Method to Generate a Patient-Specific Finite Element Model of the Human Buttocks

2008· article· en· W2108442930 on OpenAlexaff
Éric Wagnac, Carl‐Éric Aubin, Jean Dansereau

Bibliographic record

VenueIEEE Transactions on Biomedical Engineering · 2008
Typearticle
Languageen
FieldHealth Professions
TopicPressure Ulcer Prevention and Management
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsCushionButtocksWheelchairFinite element methodSittingInternal pressurePosition (finance)Structural engineeringMaterials sciencePressure soresStress (linguistics)Biomedical engineeringEngineeringComputer scienceComposite materialSurgeryMedicine

Abstract

fetched live from OpenAlex

Finite element (FE) models are very efficient tools to study internal stresses in human structures that induce severe pressure sores. Unfortunately, methods currently used to generate FE models are not suitable for clinical application involving wheelchair users. A clinical-oriented method, based on calibrated-biplanar radiographs, was therefore developed to generate a subject-specific FE model of the buttocks in a non-weighted sitting position. The model was then used to analyze the stress distribution within the buttocks and compare two wheelchair seat cushions designs. Additional radiographs and pressure measurements in a weighted sitting position were acquired to validate the FE model experimentally. Results from the FE model were in good agreement with experimental data and related literature. An internal peak pressure of 45.3 kPa was observed while seated on a flat foam cushion, corresponding to an interface pressure of 23.6 kPa. Both pressures occurred underneath the ischial tuberosities. When compared to the flat foam cushion, the contoured foam cushion reduced internal and interface peak pressures by 18% and 33%, respectively. The method developed in this study has a great potential for clinical use. The FE model, by predicting realistic stress distributions, allows for the selection of a convenient wheelchair seat cushion.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.907
Threshold uncertainty score0.497

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 head0.054
GPT teacher head0.346
Teacher spread0.292 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations35
Published2008
Admission routes1
Has abstractyes

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