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ReadySim : A computational framework for building explicit finite element musculoskeletal simulations directly from motion laboratory data
Author(s) -
Hume Donald R.,
Rullkoetter Paul J.,
Shelburne Kevin B.
Publication year - 2020
Publication title -
international journal for numerical methods in biomedical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.741
H-Index - 63
eISSN - 2040-7947
pISSN - 2040-7939
DOI - 10.1002/cnm.3396
Subject(s) - kinematics , computer science , finite element method , software , python (programming language) , computational model , computational science , joint (building) , simulation , structural engineering , engineering , physics , classical mechanics , programming language , operating system
Musculoskeletal modeling allows researchers insight into joint mechanics which might not otherwise be obtainable through in vivo or in vitro studies. Common musculoskeletal modeling techniques involve rigid body dynamics software which often employ simplified joint representations. These representations have proven useful but are limited in performing single‐framework deformable analyzes in structures of interest. Musculoskeletal finite element (MSFE) analysis allows for representation of structures in sufficient detail to obtain accurate solutions of the internal stresses and strains including complex contact conditions and material representations. Studies which performed muscle force optimization directly in a finite element framework were often limited in complexity to minimize computational time. Recent advances in computational efficiency and control schemes for muscle force prediction have made these solutions more practical. Yet, the formulation of subject‐specific simulations remains a challenging problem. The objectives of this work were to develop an open‐source computational framework to build and run simulations which (a) scale the size of MSFE models and efficiently estimate (b) joint kinematics and (c) muscle forces from human motion data collected in a typical gait laboratory. A computational framework was built using MATLAB and Python to interface with model input and output files. The software uses laboratory marker data to scale model segment lengths and estimate joint kinematics. Concurrent muscle force and tissue strain estimations are performed based on the estimated kinematics and ground reaction forces. This software will improve the usability and consistency of single‐framework MSFE simulations. Both software and template model are made freely available on SimTK. Novelty Statement Single framework musculoskeletal modeling directly in a finite element environment for muscle force estimation and tissue strain analysis. Open dissemination of unilateral musculoskeletal finite element model and software used in manuscript