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Automated creation and tuning of personalised muscle paths for OpenSim musculoskeletal models of the knee joint

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Abstract

Computational modelling is an invaluable tool for investigating features of human locomotion and motor control which cannot be measured except through invasive techniques. Recent research has focussed on creating personalised musculoskeletal models using population-based morphing or directly from medical imaging. Although progress has been made, robust definition of two critical model parameters remains challenging: (1) complete tibiofemoral (TF) and patellofemoral (PF) joint motions, and (2) muscle tendon unit (MTU) pathways and kinematics (i.e. lengths and moment arms). The aim of this study was to develop an automated framework, using population-based morphing approaches to create personalised musculoskeletal models, consisting of personalised bone geometries, TF and PF joint mechanisms, and MTU pathways and kinematics. Informed from medical imaging, personalised rigid body TF and PF joint mechanisms were created. Using atlas- and optimisation-based methods, personalised MTU pathways and kinematics were created with the aim of preventing MTU penetration into bones and achieving smooth MTU kinematics that follow patterns from existing literature. This framework was integrated into the Musculoskeletal Atlas Project Client software package to create and optimise models for 6 participants with incrementally increasing levels of personalisation with the aim of improving MTU kinematics and pathways. Three comparisons were made: (1) non-optimised (Model 1) and optimised models (Model 3) with generic joint mechanisms; (2) non-optimised (Model 2) and optimised models (Model 4) with personalised joint mechanisms; and (3) both optimised models (Model 3 and 4). Following optimisation, improvements were consistently shown in pattern similarity to cadaveric data in comparison (1) and (2). For comparison (3), a number of comparisons showed no significant difference between the two compared models. Importantly, optimisation did not produce statistically significantly worse results in any case.

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Availability of data materials

The pre-existing MAP-Client is freely available here: https://map-client.readthedocs.io/en/latest/with additional information provided here https://simtk.org/projects/map. Note the framework is currently only available in Python 2, an updated version for Python 3 is currently being produced by the original developers. Updates regarding the status of this update will be provided on the above SimTK link. The developed frame generated as part of this research is available upon reasonable request from the corresponding author. The models generated as part of this research are available upon reasonable request.

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Funding

The authors would like to acknowledge the funding from a PhD scholarship from Griffith University.

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Authors and Affiliations

  1. Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute (ADAPT), Griffith University, Gold Coast, QLD, Australia

    B. A. Killen, S. Brito da Luz, D. G. Lloyd & D. J. Saxby

  2. School of Allied Health Sciences, Griffith University, Gold Coast, QLD, Australia

    B. A. Killen, S. Brito da Luz, D. G. Lloyd & D. J. Saxby

  3. Human Movement Biomechanics Research Group, Department of Movement Sciences, KU Leuven, Leuven, Belgium

    B. A. Killen

  4. Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand

    A. D. Carleton, J. Zhang & T. F. Besier

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  1. B. A. Killen
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  2. S. Brito da Luz
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  3. D. G. Lloyd
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  7. D. J. Saxby
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Correspondence to B. A. Killen.

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Killen, B.A., Brito da Luz, S., Lloyd, D.G. et al. Automated creation and tuning of personalised muscle paths for OpenSim musculoskeletal models of the knee joint. Biomech Model Mechanobiol 20, 521–533 (2021). https://doi.org/10.1007/s10237-020-01398-1

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  • DOI: https://doi.org/10.1007/s10237-020-01398-1

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