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Open AccessJournal ArticleDOI

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

TLDR
Practical guidelines for verification and validation of NMS models and simulations are established that researchers, clinicians, reviewers, and others can adopt to evaluate the accuracy and credibility of modeling studies.
Abstract
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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Citations
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Journal ArticleDOI

Full-Body Musculoskeletal Model for Muscle-Driven Simulation of Human Gait

TL;DR: An open-source 3-D musculoskeletal model with high-fidelity representations of the lower limb musculature of healthy young individuals that can be used to generate accurate simulations of gait is created.

Morphological Muscle and joint parameters for musculoskeletal modelling of the lower extremity

TL;DR: In this paper, a complete and consistent anatomical dataset containing the orientations of joints (hip, knee, ankle and subtalar joints), muscle parameters (optimum length, physiological cross sectional area), and geometrical parameters (attachment sites, ‘via’ points) was presented.
Journal ArticleDOI

Evaluation of Direct Collocation Optimal Control Problem Formulations for Solving the Muscle Redundancy Problem

TL;DR: The present approach lacks some of the major limitations of established methods such as static optimization and computed muscle control while remaining computationally efficient.
Journal ArticleDOI

Neural Data-Driven Musculoskeletal Modeling for Personalized Neurorehabilitation Technologies

TL;DR: The ability of using electrophysiological recordings to inform biomechanical models enables accessing a broader range of neuromechanical variables than analyzing electrophYSiological data or movement data individually, which enables understanding the neuromuscular interplay underlying in vivo movement function, pathology, and robot-assisted motor recovery.
References
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OpenSim: Open-Source Software to Create and Analyze Dynamic Simulations of Movement

TL;DR: OpenSim is developed, a freely available, open-source software system that lets users develop models of musculoskeletal structures and create dynamic simulations of a wide variety of movements to simulate the dynamics of individuals with pathological gait and to explore the biomechanical effects of treatments.
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Structural Reliability: Analysis and Prediction

TL;DR: Measures of Structural Reliability Assessment, including second-Moment and Transformation Methods, and Probabilistic Evaluation of Existing Structures.
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