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Overview

There is no scientific consensus on when a simulation is "good enough".  Ultimately, you need to be sure you are asking the right question (such as “which muscles can contribute to knee flexion in this posture?”) and that your results are robust to variations in model parameters. In general, you should avoid questions with absolute finite answers (e.g., “how much force was generated?”) and instead use musculoskeletal simulations to understand relationships between model parameters and components. 

Nonetheless, evaluating your results is one of the most important elements of generating and analyzing a simulation of human movement. In the sections below, we provide a set of best practices for using each of the tools in the OpenSim pipeline. These best practices are intended as a starting point to help you make sure you are collecting good data and analyzing and evaluating it effectively. This list is by no means exhaustive and depends highly on the nature of the motion you are studying and the research questions you are asking. 

We've also provided a short checklist to use when evaluating your simulation.

Scaling a Model

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_Scaling Best Practices
_Scaling Best Practices

Inverse Kinematics

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_Inverse Kinematics Best Practices
_Inverse Kinematics Best Practices

Inverse Dynamics

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_Inverse Dynamics Best Practices
_Inverse Dynamics Best Practices

Static Optimization

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_Static Optimization Best Practices
_Static Optimization Best Practices

Residual Reduction

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_RRA Best Practices
_RRA Best Practices

Computed Muscle Control

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_CMC Best Practices
_CMC Best Practices

Forward Dynamics

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_Forward Dynamics Best Practices
_Forward Dynamics Best Practices

Contributors

Stanford University - Jennifer Hicks, Ajay Seth, Sam Hamner, Matt DeMers

University of Delaware - Jill Higginson, Brian Knarr, Amber Collins, Elisa Schrank, Chris Henderson