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Record W3169870601

A Validated Cohesive Finite Element Analysis of Needle Insertion into Human Skin

2021· article· en· W3169870601 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCMBES Proceedings · 2021
Typearticle
Languageen
FieldMedicine
TopicDiabetic Foot Ulcer Assessment and Management
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsFinite element methodMaterials scienceStiffnessCohesive zone modelTraction (geology)Structural engineeringProcess (computing)Biomedical engineeringMechanical engineeringComposite materialComputer scienceEngineering
DOInot available

Abstract

fetched live from OpenAlex

Medical needles play important roles in many diagnostic and therapeutic applications. To design needles and procedures involving needles more efficiently, the investigation of the needle insertion process and the related parameters are key to developing related novel technologies. This paper provides a two-dimensional finite element model of needle insertion into the human skin, which is validated with available experimental results in the literature. The crack propagation in the tissue is modelled via the cohesive zone method. To this end, a curve-fitting approach based on the reaction force applied to the needle during the insertion is exploited to optimize cohesive parameters. Our simulations show that failure traction of 2 MPa, initial stiffness of 4000 MPa/mm, and separation length of 1.6 mm lead to a reliable model compared to the experimental results.  We also investigated the effect of needle diameter on the insertion force.

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.

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 score0.045
Threshold uncertainty score0.587

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.301
Teacher spread0.284 · 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