AboutDownloadsForumsSource Code
Modenese, L. and J.-B. Renault. "Automatic Generation of Personalised Skeletal Models of the Lower Limb from Three-Dimensional Bone Geometries." Journal of Biomechanics. 116: 110186 (2021)
Abstract    View

The generation of personalised and patient-specific musculoskeletal models is currently a cumbersome and time-consuming task that normally requires several processing hours and trained operators. We believe that this aspect discourages the use of computational models even when appropriate data are available and personalised biomechanical analysis would be beneficial. In this paper we present a computational tool that enables the fully automatic generation of skeletal models of the lower limb from three-dimensional bone geometries, normally obtained by segmentation of medical images. This tool was evaluated against four manually created lower limb models finding remarkable agreement in the computed joint parameters, well within human operator repeatability. The coordinate systems origins were identified with maximum differences between 0.5 mm (hip joint) and 5.9 mm (subtalar joint), while the joint axes presented discrepancies between 1° (knee joint) to 11° (subtalar joint). To prove the robustness of the methodology, the models were built from four datasets including both genders, anatomies ranging from juvenile to elderly and bone geometries reconstructed from high-quality computed tomography as well as lower-quality magnetic resonance imaging scans. The entire workflow, implemented in MATLAB scripting language, executed in seconds and required no operator intervention, creating lower extremity models ready to use for kinematic and kinetic analysis or as baselines for more advanced musculoskeletal modelling approaches, of which we provide some practical examples. We auspicate that this technical advancement, together with upcoming progress in medical image segmentation techniques, will promote the use of personalised models in larger-scale studies than those hitherto undertaken.

STAPLE, acronym for Shared Tools for Automatic Personalised Lower Extremity modelling, is a MATLAB toolbox that enables researchers in the biomechanical field to create models of the lower extremity from subject-specific bone geometries with minimum effort in negligible processing time. In most cases, that can be done just changing the input data in one of the provided workflow and running a MATLAB script.

Please note that STAPLE is released under a NON COMMERCIAL CC-BY-NC license and it is free to use for academic purposes only. For any other use please contact the authors.

Please note that the toolbox is still released as beta version. If you encounter any issue please report it at this link.

At this page we will release the stable versions of STAPLE. You can follow, participate and contribute to the open development of the toolbox at https://github.com/modenaxe/msk-STAPLE.

License: STAPLE Toolbox

STAPLE requires three-dimensional bone geometries as an input. These geometries are normally surface models segmented from medical images like magnetic resonance imaging (MRI) or computed tomography (CT) scans. STAPLE performs morphological analyses on the provided bone geometries and defines reference systems used to create models of entire legs or few joints, depending on the available data or the research intent. Currently the toolbox creates kinematic and kinetic skeletal models but will soon be extended with complete musculoskeletal capabilities.

Using STAPLE is currently possible to perform the following operations:

  • Creating complete skeletal models of the lower limb from segmented bone geometries with provided workflows or customizable degrees of freedom for the joints.

  • Creating partial skeletal models of the lower limb. For example models of hip, knee and ankle joints can be created as individual models.

  • Extracting the articular surfaces of the lower limb joints, for example the tibiofemoral articular surfaces.

  • Merging generic and personalised models.

  • Basic identification of bony landmarks, intended as first guess for registration with gait analysis motion capture data.


The latest stable version of the STAPLE toolbox is here provided.

See all Downloads