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)