We are creating tools for developing and interpreting subject-specific
dynamic simulations of normal and abnormal human movement.
We combine dynamic simulation with control algorithms, including computed-muscle
control, optimal control, and EMG-Driven methods. |
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Computed
Muscle Control
We have developed a new algorithm, which we call computed
muscle control, that uses static optimization along with feedforward
and feedback controls to drive the kinematic trajectory of a musculoskeletal
model toward a set of desired kinematics. |
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EMG-Driven
Electromyography (EMG) can be used to estimate muscle activation
patterns, which can be used in both forward and inverse-dynamics calculations
to estimate muscle forces and joint moments. |
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Optimal
Control
We have used optimal control methods to study coordination and control
of the standing long jump and walking. |
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Analysis
of Simulations
Once a simulation of movement is generated and tested, the
simulation can be analyzed to gain insight into neuromuscular function.
The contributions of individual muscles to the joint moments, joint
angular accelerations, ground reaction forces, segmental energies,
and other variables of interest can be determined. |
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Contact
Modeling
We use rigid and elastic contact modeling to predict the motions of
knee implants during a stepup activity. |
