A challenging aspect of subject specific musculoskeletal modeling is the estimation of muscle parameters, especially optimal fiber length and tendon slack length. In this study, the method for scaling musculotendon parameters published by Winby et al. (2008), Journal of Biomechanics 41, 1682-1688, has been reformulated, generalized and applied to two cases of practical interest: 1) the adjustment of muscle parameters in the entire lower limb following linear scaling of a generic model and 2) their estimation “from scratch” in a subject specific model of the hip joint created from medical images. In the first case, the procedure maintained the muscles’ operating range between models with mean errors below 2.3% of the reference model normalized fiber length value. In the second case, a subject specific model of the hip joint was created using segmented bone geometries and muscle volumes publicly available for a cadaveric specimen from the Living Human Digital Library (LHDL). Estimated optimal fiber lengths were found to be consistent with those of a previously published dataset for all 27 considered muscle bundles except gracilis. However, computed tendon slack lengths differed from tendon lengths measured in the LHDL cadaver, suggesting that tendon slack length should be determined via optimization in subject-specific applications. Overall, the presented methodology could adjust the parameters of a scaled model and enabled the estimation of muscle parameters in newly created subject specific models. All data used in the analyses are of public domain and a tool implementing the algorithm is available at https://simtk.org/home/opt_muscle_par.
This project aims to make available a tool for muscle parameters (optimal fiber length and tendon slack length) adjustment and estimation.
Estimation of optimal fiber length and tendon slack length in Hill-type muscle models included in musculoskeletal models can be challenging. This project presents an optimization based technique to adjust muscle parameters of models linearly scaled from a generic one and to obtain reasonable estimation of optimal fiber lengths and tendon slack lengths in models generated from medical images.
An OpenSim plugin implementing this approach is available at the following GitHub repository: https://github.com/MuscleOptimizer
The documentation for the plugin is available online at http://muscleoptimizer.github.io/MuscleOptimizer
A generic MATLAB tool implementing this approach is also available at: https://github.com/modenaxe/MuscleParamOptimizer
This project will make available an OpenSim plugin and equivalent Matlab tools for estimating optimal fiber lengths and tendon slack lengths via an optimization procedure in subject specific models.See all Downloads