RESUMO
High quality simulations of the dynamics of soft flexible objects can be rather costly, because the assembly of internal forces through an often nonlinear stiffness at each time step is expensive. Many standard implicit integrators introduce significant, time-step dependent artificial damping. Here we propose and demonstrate the effectiveness of an exponential Rosenbrock-Euler (ERE) method which avoids discretization-dependent artificial damping. The method is relatively inexpensive and works well with the large time steps used in computer graphics. It retains correct qualitative behaviour even in challenging circumstances involving non-convex elastic energies. Our integrator is designed to handle and perform well even in the important cases where the symmetric stiffness matrix is not positive definite at all times. Thus we are able to address a wider range of practical situations than other related solvers. We show that our system performs efficiently for a wide range of soft materials.
RESUMO
We describe a methodology to qualitatively and quantitatively determine the activation level of individual muscles by voltage measurements from an array of voltage sensors on the skin surface. A physical finite element model for electrostatics simulation is constructed from morphometric data and numerical inversion techniques are used to determine muscle activation patterns. Preliminary results from experiments with simulated and human data are presented for activation reconstructions of three muscles in the upper arm (biceps brachii, bracialis, and triceps). This approach potentially offers a new clinical tool to sensitively assess muscle function in patients suffering from neurological disorders (e.g., spinal cord injury) and could more accurately guide advances in the evaluation of specific rehabilitation training regimens.
