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Kinematic behavior of a customized surface-guided knee implant during simulated knee-bending

2017· article· en· W2734110340 on OpenAlexaff
Shabnam Pejhan, Éric Bohm, Jan-Mels Brandt, Trevor C. Gascoyne, U.P. Wyss

Bibliographic record

VenueMedical Engineering & Physics · 2017
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsConcordia UniversityOrthopaedic Innovation CentreConcordia HospitalUniversity of Manitoba
Fundersnot available
KeywordsSquatting positionKinematicsCondyleRotation (mathematics)Translation (biology)OrthodonticsMaterials scienceMedicineBiomedical engineeringAnatomyMathematicsGeometryPhysics

Abstract

fetched live from OpenAlex

Different designs of total knee replacements (TKRs) aim to enhance the satisfaction of the patients by providing close to normal kinematics. In the surface-guided TKRs, the guidance of the motion in a normal pattern should be achieved through specially shaped articulating geometries. This study used virtual simulation along with a load-controlled knee wear simulator to evaluate the kinematic performance of a customized surface-guided TKR under weight-bearing conditions of lunging and squatting activities. The outcome pattern of TKR motion almost agreed with the predefined design target. The tibial insert rotated internally through a maximum angle of 10.6° and 19.94° for the experimentally simulated lunging and squatting cycles, respectively. This rotation occurred around a medial center, as indicated by a small amount of posterior translation of the medial condyle (maximum of 2.5mm and 6.4mm for lunging and squatting) versus the posterior translation of the lateral condyle (maximum of 12mm and 24.2mm for lunging and squatting). The contact forces mainly provided the guidance of the motion at the tibiofemoral articulating surfaces.The normalized root mean square error between outcomes of the virtual simulations and tests for the angle of internal-external rotation of the tibial insert was less than 8% for one cycle of lunging and squatting. These measures confirm the validity of the virtual simulation for future evaluations of the customized surface-guided TKRs.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.593
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.017
GPT teacher head0.285
Teacher spread0.268 · 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.

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

Citations3
Published2017
Admission routes1
Has abstractyes

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