MétaCan
Menu
← Back to cohort
Record W4390660665 · doi:10.1101/2024.01.06.574467

Development and validation of a subject-specific integrated finite element musculoskeletal model of human trunk with ergonomic and clinical applications

2024· preprint· en· W4390660665 on OpenAlexafffund
Farshid Ghezelbash, Amir Hossein Eskandari, A. Shirazi‐Adl, Christian Larivière

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsInstitut de recherche Robert-Sauvé en santé et en sécurité du travailPolytechnique Montréal
FundersMitacsInstitut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail
KeywordsTorsoContext (archaeology)TrunkBiomechanicsFinite element methodComputer scienceBiomedical engineeringLow back painParametric statisticsPhysical medicine and rehabilitationEngineeringMedicineStructural engineeringAnatomyMathematics

Abstract

fetched live from OpenAlex

Abstract Background and Objectives Biomechanical modeling of the human trunk is crucial for understanding spinal mechanics and its role in ergonomics and clinical interventions. Traditional models have been limited by only considering the passive structures of the spine in finite element (FE) models or incorporating active muscular components in multi-body musculoskeletal (MS) models with an oversimplified spine. This study aimed to develop and validate a subject-specific coupled FE-MS model of the trunk that integrates detailed representation of both the passive and active components for biomechanical simulations. Methods We constructed a parametric FE model of the trunk, incorporating a realistic muscle architecture, personalized through imaging datasets and statistical shape models. To validate the model, we compared tissue-level responses with in vitro experiments, and muscle activities and intradiscal pressures versus in vivo measurements during various physical activities. We further demonstrated the versatility of the proposed personalized integrated framework through additional applications in ergonomics (i.e., wearing an exoskeleton) and surgical interventions (e.g., nucleotomy and spinal fusion). Results The model demonstrated satisfactory agreement with experimental data, showcasing its validity to predict tissue- and disc-level responses accurately, as well as muscle activity and intradiscal pressures. When simulating ergonomics scenarios, the exoskeleton-wearing condition resulted in lower intradiscal pressures (1.9 MPa vs. 2.2 MPa at L4-L5) and peak von Mises stresses in the annulus fibrosus (2.2 MPa vs. 2.9 MPa) during forward flexion. In the context of surgical interventions, spinal fusion at L4-L5 led to increased intradiscal pressure in the adjacent upper disc (1.72 MPa vs. 1.58 MPa), whereas nucleotomy minimally influenced intact disc pressures but significantly altered facet joint loads and annulus fibrosus radial strains. Conclusions The integrated FE-MS model of the trunk represents a significant advancement in biomechanical simulations, providing insights into the intricate interplay between active and passive spinal components. Its predictive capability extends beyond that of conventional models, enabling detailed risk analysis and the simulation of varied surgical outcomes. This comprehensive tool has potential implications for the design of ergonomic interventions and the optimization of surgical techniques to minimize detrimental effects on spinal mechanics.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.033
GPT teacher head0.291
Teacher spread0.258 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2024
Admission routes2
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)→Same topicSpine and Intervertebral Disc Pathology→French-language works237,207→