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This Tutorial is for use with OpenSim 4.0 and above. Please refer to the OpenSim Download page to get the required version. |
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| User Guide Readings | Prerequisite Tutorials | Helpful Readings |
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The aim of Study 2 is to assess how improving the input kinematics effects that muscle activations and forces that Static Optimization outputs. Static Optimization is trying to compute muscle forces that generate the accelerations seen in the input kinematics. If these accelerations are noisy, there will be noise in the muscle activations and forces. In Study 1 we saw noisy activations and forces that are most likely the result of noisy motion data. We will investigate two methods for improving the motion data: (i) filtering the input kinematics and (ii) using the Residual Reduction Algorithm (RRA) to smooth the kinematics.
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Since RRA uses a forward dynamics simulation (i.e., the model's equations of motion are integrated forward in time), the output kinematics will be consistent accelerations that are great to use in Static Optimization. If you are using RRA results, you don't need to do any additional filtering. Using RRA also has the added benefit of generating a more "dynamically consistent" model and set of kinematics and forces. We are not going to go in depth into RRA in this particular tutorial so if you are unfamiliar with RRA please refer to the User's Guide. You can also complete the tutorial The Strength of Simulation: Estimating Leg Muscle Forces in Stance and Swing to learn more about how to use and troubleshoot with RRA.
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