Details

  • Title: Muscle-Driven Simulations and Experimental Data of Cycling
  • Speakers: Caitlin Clancy, Stanford University
  • Time: Wednesday, April 17, 2024 at 9:00 AM Pacific Time

Abstract

Musculoskeletal simulations have provided valuable insights in studies of walking and running, but a set of freely available simulations and corresponding experimental data for cycling do not exist. The aim of this work was to use open-source musculoskeletal simulation softwares OpenSim and OpenSim Moco to develop a set of muscle-driven simulations of 16 participants cycling over a range of powers and cadences and validate them by comparison with experimental data.

In the first half of the webinar, Ms. Clancy will present her OpenSim modeling pipeline for cycling and the results of her study. She will demonstrate her team’s approach to generating simulations using OpenSim Moco and how they explored different optimization objectives to improve similarity with experimental data.

In the second half of the webinar, Ms. Clancy will discuss best practices for, and share lessons learned from, working with OpenSim Moco. In particular, she will discuss strategies and provide examples she used to iterate and refine the Moco optimization problem and choose different settings.


Clancy, C.E.*, Gatti, A.A.*, Ong, C.F., Maly, M.R., Delp, S.L. Muscle-driven simulations and experimental data of cycling. Sci Rep 13, 21534 (2023). https://doi.org/10.1038/s41598-023-47945-5 *Authors contributed equally.

This webinar is offered jointly with the Restore Center, an NIH-funded Medical Rehabilitation Research Resource Network Center at Stanford University.


Our Speaker

Caitlin Clancy

Senior Mechanical Engineer

Caitlin Clancy is currently a Senior Modeling & Simulation Engineer at Johnson & Johnson in the surgical robotics division. She is passionate about using computational modeling, simulation, and analysis to solve problems in medical and healthcare technology. Caitlin received her M.S. in Mechanical Engineering at Stanford University with concentrations in biomechanics and materials & stress analysis and her B.S. in Mechanical Engineering at Johns Hopkins University. Her graduate school research centered on computational musculoskeletal modeling and simulation using optimal control methods with OpenSim under Dr. Scott Delp in the Neuromuscular Biomechanics Lab (NMBL). Prior to graduate school, she worked in industry as a Mechanical Structural Analyst using finite element analysis methods.

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