Automated optimization of residual reduction algorithm parameters in OpenSim

• Main Authors: Pickle, N.T (Author), Silverman, A.K (Author), Sturdy, J.T (Author)
• Format: Article
• Language: English
• Published: Elsevier Ltd 2022
• Subjects: algorithm; Algorithm parameters; article; Automated optimization; biomechanics; Biomechanics; Biophysics; data analysis software; decision making; Decision making; documentation; Dynamic consistencies; Dynamic Consistency; Ground reaction forces; Kinematics; MATLAB; Movement simulation; Movement Simulation; Musculoskeletal modeling; OpenSim; Optimization; Python; Reduction algorithms; Residual error; Residual reduction algorithm; RRA; simulation
• Online Access: View Fulltext in Publisher

 The residual reduction algorithm (RRA) in OpenSim is designed to improve dynamic consistency of kinematics and ground reaction forces in movement simulations of musculoskeletal models. RRA requires the user to select numerous tracking weights for the joint kinematics to reduce residual errors. Selection is often performed manually, which can be time-consuming and is unlikely to yield optimal tracking weights. A multi-heuristic optimization algorithm was used to expedite tracking weight decision making to reduce residual errors. This method produced more rigorous results than manual iterations and although the total computation time was not significantly reduced, this method does not require the user to monitor the algorithm's progress to find a solution, thereby reducing manual tuning. Supporting documentation and code to implement this optimization is freely provided to assist the community with developing movement simulations. © 2022 Elsevier Ltd