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The human shoulder plays an important role in human posture and motion, especially in scenarios in which humans need achieve tasks with external loads. The shoulder complex model is critical in digital human modeling and simulation because a fidelity model is the basis for realistic posture and motion predictions for digital humans. The complexity of the shoulder mechanism makes it difficult to model a shoulder complex realistically. Although many researchers have attempted to model the human shoulder complex, there has not been a survey of these models and their benefits and limitations. This paper attempts to review various biomechanical models proposed and summarize the pros and cons. It focuses mainly on the human modeling domain, although some of these models were originally from the robotics field. The models are divided into two major categories: open-loop chain models and closed-loop chain models.

Over the past several years, significant advances have been made in the area of posture prediction. However, to make simulations more useful for vehicle design, additional unique tools are needed. This research focuses on the development of one such tool, called zone differentiation. This new tool allows user to visualize not only the complete reach envelope but also the interior comfort levels of the envelope. It uses a color map to display the relative values of various performance measures (i.e. comfort) at points surrounding an avatar. This is done by leveraging an optimization-based approach to posture prediction. Using this tool, a vehicle designer can visually display the impact that the placement of a control (switch, button, etc.) has on a driver's postural comfort. The comfort values are displayed in a manner similar to how a finite element analysis (FEA) programs display stress and strain results. The development of this tool requires two main components.

Presented in this paper is an on-going project to develop a new generation of virtual human models that are highly realistic in terms of appearance, movement, and feedback (evaluation of the human body during task execution). Santos™ is an avatar that exhibits extensive modeling and simulation capabilities. It is an anatomically correct human model with more than 100 degrees of freedom. Santos™ resides in a virtual environment and can conduct human-factors analysis. This analysis entails, among other things, posture prediction, motion prediction, gait analysis, reach envelope analysis, and ergonomics studies. There are essentially three stages to developing virtual humans: (1) basic human modeling (representing how a human functions independently), (2) input functionality (awareness and analysis of the human’s environment), and (3) intelligent reaction to input (memory, reasoning, etc.). This paper addresses the first stage.