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Are Subject-Specific Musculoskeletal Models Robust to the Uncertainties in Parameter Identification?

Figure 2

Schematic of statistical perturbation of the input variables.

To analyze the sensitivity of model predictions to the uncertainties in parameter values, three categories of stochastic input variables were identified (for a total of 312 input variables): body landmark positions (affecting position and orientation of body reference frames and joints, inertial tensors and joint kinematics), musculotendon geometry (position of origin/insertion and via points defining musculotendon paths and affecting muscle moment arms) and maximum muscle tension (affecting maximum force-generating capacity of the muscles). Each variable was assumed as normally or uniformly distributed, and a Latin Hypercube Sampling strategy was applied to efficiently sample the variables from their distribution.

Figure 2