Validation of computational models in biomechanics

Henninger, Heath B.; Reese, Shawn P.; Anderson, Andrew E.; Weiss, Jeffrey A.

doi:10.1243/09544119jeim649

Cited by 154 publications

(115 citation statements)

References 63 publications

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“…Although the prediction accuracy is considerably high both for strains (R 2 >0.95, (Schileo et al, 2008;Yosibash et al, 2007)) and femoral strength (standard error of estimation(SEE)<400 N, (Koivumäki et al, 2012)), FE models have not yet been introduced in clinical practice. This is due to several reasons including concerns about validation (Henninger et al, 2010;Viceconti et al, 2005). Typically, validation against ex-vivo measurements with strain-gauges is performed.…”

Section: Introductionmentioning

confidence: 99%

How accurately can subject-specific finite element models predict strains and strength of human femora? Investigation using full-field measurements

Grassi

Väänänen

Ristinmaa

et al. 2016

Journal of Biomechanics

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Subject-specific finite element models have been proposed as a tool to improve fracture risk assessment in individuals. A thorough laboratory validation against experimental data is required before introducing such models in clinical practice. Results from digital image correlation can provide full-field strain distribution over the specimen surface during in vitro test, instead of at a few pre-defined locations as with strain gauges. The aim of this study was to validate finite element models of human femora against experimental data from three cadaver femora, both in terms of femoral strength and of the full-field strain distribution collected with digital image correlation. The results showed a high accuracy between predicted and measured principal strains (R 2 =0.93, RMSE=10%, 1600 validated data points per specimen). Femoral strength was predicted using a rate dependent material model with specific strain limit values for yield and failure. This provided an accurate prediction (<2% error) for two out of three specimens.In the third specimen, an accidental change in the boundary conditions occurred during the experiment, which compromised the femoral strength validation. The achieved strain accuracy was comparable to that obtained in state-of-the-art studies which validated their prediction accuracy against 10-16 strain gauge measurements. Fracture force was accurately predicted, with the predicted failure location being very close to the experimental fracture rim. Despite the low sample size and the single loading condition tested, the present combined numerical-experimental method showed that finite element models can predict femoral strength by providing a thorough description of the local bone mechanical response.

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Section: Introductionmentioning

confidence: 99%

How accurately can subject-specific finite element models predict strains and strength of human femora? Investigation using full-field measurements

Grassi

Väänänen

Ristinmaa

et al. 2016

Journal of Biomechanics

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“…Most biomechanics researchers are aware of the importance of validation, but the field lacks best practices for the challenging process of verifying and validating NMS models and simulations. Several papers [3][4][5] have laid the groundwork, identifying principles and considerations, but these papers stop short of providing specific guidelines for NMS modeling and simulation. The knowledge and practices of how to best validate a biomechanical model and verify modeling software used in past research studies have not been adequately synthesized.…”

Section: Introductionmentioning

confidence: 99%

Is My Model Good Enough? Best Practices for Verification and Validation of Musculoskeletal Models and Simulations of Movement

Hicks

Uchida

Seth

et al. 2015

Journal of Biomechanical Engineering

554

455

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Computational modeling and simulation of neuromusculoskeletal (NMS) systems enables researchers and clinicians to study the complex dynamics underlying human and animal movement. NMS models use equations derived from physical laws and biology to help solve challenging real-world problems, from designing prosthetics that maximize running speed to developing exoskeletal devices that enable walking after a stroke. NMS modeling and simulation has proliferated in the biomechanics research community over the past 25 years, but the lack of verification and validation standards remains a major barrier to wider adoption and impact. The goal of this paper is to establish practical guidelines for verification and validation of NMS models and simulations that researchers, clinicians, reviewers, and others can adopt to evaluate the accuracy and credibility of modeling studies. In particular, we review a general process for verification and validation applied to NMS models and simulations, including careful formulation of a research question and methods, traditional verification and validation steps, and documentation and sharing of results for use and testing by other researchers. Modeling the NMS system and simulating its motion involves methods to represent neural control, musculoskeletal geometry, muscle-tendon dynamics, contact forces, and multibody dynamics. For each of these components, we review modeling choices and software verification guidelines; discuss variability, errors, uncertainty, and sensitivity relationships; and provide recommendations for verification and validation by comparing experimental data and testing robustness. We present a series of case studies to illustrate key principles. In closing, we discuss challenges the community must overcome to ensure that modeling and simulation are successfully used to solve the broad spectrum of problems that limit human mobility.

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“…However, the clinical incidence of the biomechanical results obtained from computational models should be correctly interpreted by an interdisciplinary team before its predictions can be considered to have any real clinical confidence [37]. The validated computational model of a canine mandible representing the biomechanical effect of a BTDO surgical procedure may have two main impacts: (1) the significance of the observed correlations between predicted and measured strains shows that the stress patterns obtained from the FEM are an accurate predictor of the biomechanical responses of the dog mandible affected by BTDO; (2) our experimental results can be used in the future by other authors as a way for indirect validation of computational models of canine mandibles under BTDO procedures [38].…”

Section: Discussionmentioning

confidence: 98%

Biomechanics of the Canine Mandible During Bone Transport Distraction Osteogenesis

Zapata

Dechow

Watanabe

et al. 2014

Journal of Biomechanical Engineering

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This study compared biomechanical patterns between finite element models (FEMs) and a fresh dog mandible tested under molar and incisal physiological loads in order to clarify the effect of the bone transport distraction osteogenesis (BTDO) surgical process. Three FEMs of dog mandibles were built in order to evaluate the effects of BTDO. The first model evaluated the mandibular response under two physiological loads resembling bite processes. In the second model, a 5.0 cm bone defect was bridged with a bone transport reconstruction plate (BTRP). In the third model, new regenerated bony tissue was incorporated within the defect to mimic the surgical process without the presence of the device. Complementarily, a mandible of a male American foxhound dog was mechanically tested in the laboratory both in the presence and absence of a BTRP, and mechanical responses were measured by attaching rosettes to the bone surface of the mandible to validate the FEM predictions. The relationship between real and predicted values indicates that the stress patterns calculated using FEM are a valid predictor of the biomechanics of the BTDO procedures. The present study provides an interesting correlation between the stiffness of the device and the biomechanical response of the mandible affected for bone transport.

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Validation of computational models in biomechanics

Cited by 154 publications

References 63 publications

How accurately can subject-specific finite element models predict strains and strength of human femora? Investigation using full-field measurements

How accurately can subject-specific finite element models predict strains and strength of human femora? Investigation using full-field measurements

Is My Model Good Enough? Best Practices for Verification and Validation of Musculoskeletal Models and Simulations of Movement

Biomechanics of the Canine Mandible During Bone Transport Distraction Osteogenesis

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