Musculoskeletal Modeling

We use advanced musculoskeletal modeling, simulation, and optimization techniques to test hypotheses regarding the neuromuscular control of movement, estimate quantities that cannot be measured experimentally, and make individual-specific predictions to guide rehabilitation and device design.

You may be interested in working in this area if you enjoy: dynamics; optimal control; reinforcement learning

Our work in this area has been funded by the National Science Foundation (CBET/2245260, CBET/2339331 CAREER Award, and the graduate research fellowship program) 

Example Projects:

Current Projects:

• Developing a novel simulation framework that models the adaptation of neuromuscular control underlying the restoration of functional gait ability 
• Unraveling the contribution of neural control versus task constraints on muscle coordination for balance and walking (Example Papers: 1)

Past Projects: 

• Tracking simulations of walking to understand how altered patterns of muscle coordination contribute to impaired walking performance post-stroke and are remediated after rehabilitation. (Example Papers: 1, 2, 3)
• Predictive simulations of reactive balance to gain insight into why different strategies may be used to respond to unexpected perturbations to standing. (Example Papers: 1)