Interpreting Musculoskeletal Models and Dynamic Simulations: Causes and Effects of Differences Between Models

Abstract

With more than 29,000 OpenSim users, several musculoskeletal models with varying levels of complexity are available to study human gait. However, how different model parameters affect estimated joint and muscle function between models is not fully understood. The purpose of this study is to determine the effects of four OpenSim models (Gait2392, Lower Limb Model 2010, Full-Body OpenSim Model, and Full Body Model 2016) on gait mechanics and estimates of muscle forces and activations. Using OpenSim 3.1 and the same experimental data for all models, six young adults were scaled in each model, gait kinematics were reproduced, and static optimization estimated muscle function. Simulated measures differed between models by up to 6.5° knee range of motion, 0.012 Nm/Nm peak knee flexion moment, 0.49 peak rectus femoris activation, and 462 N peak rectus femoris force. Differences in coordinate system definitions between models altered joint kinematics, influencing joint moments. Muscle parameter and joint moment discrepancies altered muscle activations and forces. Additional model complexity yielded greater error between experimental and simulated measures; therefore, this study suggests Gait2392 is a sufficient model for studying walking in healthy young adults. Future research is needed to determine which model(s) is best for tasks with more complex motion.

Effects of Optimization Technique on Simulated Muscle Activations and Forces

“…Several musculoskeletal models are compatible with OpenSim to study similar movements; therefore, users must choose a model with an understanding of the implications of the differences between models. 10 Several studies have investigated the relative impact of the differences in the model parameters on the simulation results. [10][11][12][13][14] Recent work determined that differences in joint and segment coordinate system definitions and differences in muscle parameters between 3-dimensional musculoskeletal models affected simulated joint mechanics and muscle function.…”

“…10 Several studies have investigated the relative impact of the differences in the model parameters on the simulation results. [10][11][12][13][14] Recent work determined that differences in joint and segment coordinate system definitions and differences in muscle parameters between 3-dimensional musculoskeletal models affected simulated joint mechanics and muscle function. [10][11][12] In addition to model selection, users must choose an optimization technique to estimate muscle activations and forces.…”

“…[10][11][12][13][14] Recent work determined that differences in joint and segment coordinate system definitions and differences in muscle parameters between 3-dimensional musculoskeletal models affected simulated joint mechanics and muscle function. [10][11][12] In addition to model selection, users must choose an optimization technique to estimate muscle activations and forces. Open-Sim includes 2 optimization techniques, static optimization (SO) 15 and computed muscle control (CMC), 16,17 which apply different methods to estimate the muscle activations and forces that would reproduce the experimental motion.…”

“…19 Although the aforementioned studies have examined differences between the SO and CMC estimates of muscle function, these studies focused on muscle function at a single joint, 20,23 of a single muscle, 19 or a single model. 18,21,22 Given the important role of optimization techniques in uncovering the underlying muscle function responsible for movement and the known differences between musculoskeletal models in muscle function estimated by the same optimization technique, 10 there is a need to quantify the accuracy of the SO and CMC estimates of muscle forces and activations and to evaluate the combined effect of different musculoskeletal models and optimization techniques on simulated muscle function during gait. Therefore, the purpose of this study was to quantitatively compare the SO and CMC estimates of muscle activations and forces during gait to the experimental data using OpenSim and 2 associated musculoskeletal models: Gait2392 1 and the Full Body Running (Hamner) model.…”

Muscle Synergy Constraints Do Not Improve Estimates of Muscle Activity From Static Optimization During Gait for Unimpaired Children or Children With Cerebral Palsy

“…While generic models have the advantage of minimizing the amount of data that must be collected for any individual, they achieve this by including sample-based assumptions about geometry (e.g., muscle attachment points, and bone geometry) and muscle properties (e.g., activation delays, maximum muscle forces, and tendon lengths). These assumptions can have large impacts on estimated muscle activations (Correa et al, 2011;Ackland et al, 2012;Serrancolí et al, 2016;Roelker et al, 2017;Sartori et al, 2017;Żuk et al, 2018a;Hegarty et al, 2019) and may not represent individual properties (Zajac, 1989), especially for individuals not well represented by the population used to develop the models, such as children or individuals with CP (Barber et al, 2012;Barrett and Barber, 2013;Mudge et al, 2014;Handsfield et al, 2016). We found variable results across participants and muscles in both TD and CP groups emphasizing the limitations of generic musculoskeletal models to capture heterogeneity in our populations.…”