Program

Presenter: Colin Smith

This demonstration will introduce the workshop participants to using the CAMS-Knee datasets in OpenSim. It will show how to use MATLAB to prepare the necessary inputs files for OpenSim from the .csv files containing the CAMS-Knee datasets. Then, the OpenSim inverse kinematics, inverse dynamics, static optimization, and joint reaction analysis tools will be used to generate predictions of knee contact forces. This demonstration will provide a basic understanding of the structure of CAMS-Knee dataset files and the usage the basic OpenSim workflow.

Note: You must download the CAMS-Knee Datasets (.csv files) from https://cams-knee.orthoload.com/ before the workshop.

Taylor, W. R., Schütz, P., Bergmann, G., List, R., Postolka, B., Hitz, M., … & Schwachmeyer, V. (2017). A comprehensive assessment of the musculoskeletal system: the CAMS-knee data set. Journal of biomechanics, 65, 32-39.

Presenter: Colin Smith

This presentation will introduce new tools to develop multibody knee models in OpenSim with ligaments and articular contact. It will demonstrate how a multibody knee model can be developed from medical images and used for forward dynamic simulations of passive joint mechanics to replicate cadaveric experiments or laxity tests. Paraview, an open-source scientific visualization software, will be demonstrated visualize the predicted articular contact and ligament loading patterns. The first section will focus on the relevant theory and details of the OpenSim implementation of the new ligament and contact models, while the second will include a practical demo in OpenSim.

Smith, C. R., Won Choi, K., Negrut, D., & Thelen, D. G. (2018). Efficient computation of cartilage contact pressures within dynamic simulations of movement. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 6(5), 491-498.

Smith, C. R., Lenhart, R. L., Kaiser, J., Vignos, M. F., & Thelen, D. G. (2016). Influence of ligament properties on tibiofemoral mechanics in walking. The journal of knee surgery, 29(02), 099-106.

Presenter: Nick Bianco

This presentation will focus on the design, usage, and theory behind OpenSim Moco, a new software package for solving optimal control problems with OpenSim models. OpenSim Moco uses the direct collocation method to solve a wide range of biomechanics problems including motion tracking, motion prediction, and model parameter optimization. These problems are defined using a library of cost and constraint terms, and are easily customized through Matlab, Python, C++, and XML/command-line interfaces. The first section will be a brief introduction to the direct collocation method and an overview of Moco’s features and applications. The second section will include a hands-on MATLAB scripting tutorial using Moco and time for Q&A.

Dembia, C.L., Bianco, N.A., Falisse, A., Hicks, J.L., Delp, S.L. (2019). OpenSim Moco: Musculoskeletal optimal control. bioRxiv 839381, doi: https://doi.org/10.1101/839381

Project site: opensim.stanford.edu/moco

Presenter: Colin Smith 

This presentation will focus on the theory and practical usage of the COMAK simulation framework to predict functional joint mechanics during full body movement. This novel simulation tool uses measured motion capture and ground reaction force data with a musculoskeletal model including 6 DOF tibiofemoral and patellofemoral joints to predict muscle forces, ligament forces, and articular contact pressures. First, the theory behind the COMAK algorithm will be described and the results of previous sensitivity analyses and validation studies will be overviewed. Then, the features of the OpenSim implementation will be explained and a gait simulation will be performed as a practical demonstration.

Smith, C. R., Brandon, S. C., & Thelen, D. G. (2019). Can altered neuromuscular coordination restore soft tissue loading patterns in anterior cruciate ligament and menisci deficient knees during walking?. Journal of biomechanics, 82, 124-133.

Brandon, S. C., Smith, C. R., & Thelen, D. G. (2018). Simulation of soft tissue loading from observed movement dynamics. Handbook of Human Motion, 395-428.

Presentor(s): John Lloyd and Benedickt Sagl

ArtiSynth is a free, open source, Java-based 3D modeling system developed at the University of British Columbia that allows users to combine multibody and finite element (FEM) models inside a single interactive environment.  Applications have included musculoskeletal modeling (foot, lower limb, spine, arm, shoulder, knee), functional modeling of swallowing, mastication and speech, and surgical treatment planning involving the head and neck region.

This demonstration will provide an overview of ArtiSynth and its capabilities, combined with a hands-on tutorial in which attendees can evaluate how it may be used to further their research goals.

Attendees will also be able to download ArtiSynth and experiment with it beforehand. Complete information about ArtiSynth, along with instructions for installing and using it, is available at www.artisynth.org/doc/html/installation/quickInstallation.html.

Lloyd, J. E., Stavness, I., & Fels, S. (2012). ArtiSynth: A fast interactive biomechanical modeling toolkit combining multibody and finite element simulation. In Soft tissue biomechanical modeling for computer assisted surgery (pp. 355-394). Springer, Berlin, Heidelberg.

From medical images to subject-specific musculoskeletal model

Presenter: Mariska Wesseling

The outcome of dynamic simulations is very dependent on the level of subject specific detail that is used in musculoskeletal models.  Models can be personalized using medical imaging techniques, e.g. to identify the subject specific location of muscle attachments and/or bone shape. Sufficient accuracy can be achieved using medical imaging input, but the process is complicated and time consuming, where it can take up to several days to create one model. This presentation will focus on how the Mimics Innovation Suite (Mimics and 3-matic) can simplify and speed up this process and the available tools that allow for full processing of medical images to a musculoskeletal model in OpenSim.

Presentor: Bryce Killen

The collection of extensive and complete medical imaging is often an impractical option for many researchers due to inherent time, and cost burdens. An alternative to these time and cost intensive methods is the use of statistical shape models and statistical shape modelling techniques. These models allow researchers to reconstruct entire bone geometries from sparse or incomplete data. The Musculoskeletal Atlas Project (MAP) Client provides a flexible and open-source framework exactly for this purpose as well as a direct output into OpenSim. During the demonstration you will be introduced to the MAP-Client interface detailing the MAP-Client workflow and plugin structure. Following this introduction, an example workflow whereby full lower-limb geometries are reconstructed from a combination of motion capture data, and sparse medical imaging will be shown. Finally, the reconstructed bones will be compiled into a personalised OpenSim model which can be used for gait simulations.