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This paper describes an effective integrated method for estimation of subject-specific mass, inertia tensor, and center of mass of individual body segments of a digital avatar for use with physics-based digital human modeling simulation environment. One of the main goals of digital human modeling and simulation environments is that a user should be able to change the avatar (from male to female to a child) at any given time. The user should also be able to change the various link dimensions, like lengths of upper and lower arms, lengths of upper and lower legs, etc. These customizations in digital avatar's geometry change the kinematic and dynamic properties of various segments of its body. Hence, the mass and center of mass/inertia data of the segments must be updated before simulating physics-based realistic motions. Most of the current methods use mass and inertia properties calculated from a set of regression equations based on average of some population.

This paper presents an optimization-based algorithm for simulating the dynamic motion of a digital human. We also formulate the metabolic energy expenditure during the motion, which is calculated within our algorithm. This algorithm is implemented and applied to Santos™, an avatar developed at The University of Iowa. Santos™ is a part of a virtual environment for conducting digital human analysis consisting of posture prediction, motion prediction, and physiology studies. This paper demonstrates our dynamic motion algorithm within the Santos™ virtual environment. Mathematical evaluations of human performance are essential to any effort to compare various ergonomic designs. In fact, the human factors design process can be formulated as an optimization problem that maximizes human performance. In particular, an optimal design must be found while taking into consideration the effects of different motions and hand loads corresponding to a number of tasks.