Computational Modeling: Human Dynamic Model

Measurements of human activity are useful for studying the neural computations underlying human behavior. Dynamic models of human behavior also support clinical efforts to analyze, rehabilitate, and predict movements. They are used in biomechanics to understand and diagnose motor pathologies, find new motor strategies that decrease the risk of injury, and predict potential problems from a particular procedure. This paper describes a physics-based movement analysis technique for analyzing and simulating bipedal humanoid movements. A 48 degree of freedom dynamic model of humans uses physical simulation software as a tool for synthesizing humanoid movement with sufficient speed and accuracy to allow the analysis and synthesis of real-time interactive applications such as psychophysics experiments using virtual reality or human-in-the-loop teleoperation of a simulated robotic system. The dynamic model is fast and robust while still providing results sufficiently accurate to be used to believably animate a humanoid character, control a simulated system, or estimate internal joint forces used during a movement for creating effort-contingent experimental stimuli. A virtual reality environment developed as part of this research supports controlled experiments for systematically recording human behaviors.