Forward dynamic simulation provides a powerful framework for characterizing in vivo loads, for investigating the muscular coordination of movement, and for predicting changes in movement due to injury, impairment or surgical intervention. However, the computational challenge of generating simulations has greatly limited the use and application of dynamic models. Traditional approaches use optimization to determine a set of input trajectories (e.g. muscle forces or joint torques) that drive a model to track experimental motion and force measurements [1,2]. Optimization is needed, in part, to resolve dynamic inconsistencies between measured kinematics and ground reactions. Large scale dynamic optimization problems of this type are inherently difficult to solve, often necessitating model simplifications. It has previously been shown that dynamic inconsistencies can be efficiently resolved on a per-frame basis by enforcing whole-body dynamic constraints [3,4]. However, forward simulations cannot be generated from such data since integration of the accelerations will not re-produce measured velocities and positions.

This content is only available via PDF.
You do not currently have access to this content.