Driving Human Patient Simulators and Virtual Combat Casualty Charactersusing a High-Fidelity High-Speed Physiology Model Solver for Multi-Model Mixed-Reality Simulation

摘要

A scalable and extensible method for integrating a high-fidelity high-speed physiology model solver into a simulation environment to drive specific capabilities of a human patient simulator and the motions and behaviors of virtual combat casualty characters consistent with the simulated injuries sustained is presented. In addition, performance data from trial runs that took place in January of 2016 in a simulation-based training for USAF battlefield airmen involved in personnel recovery (Guardian Angels or GAs) is also presented. The need to provide a realistic degree of operational fidelity relative to exhibiting the signs and symptoms of injuries and their interventions on human patient simulators and virtual combat casualty characters is an essential component to integrating medical skills sustainment training in existing DoD simulation environments. In addition, virtual lifeforms that should sustain injuries from events taking place in the synthetic environment (such as a munition blast) are at best merely "decorated" via a texture map change to their model and exhibit uncorrelated motion and behaviors that should be informed and consistent with their injuries. This lack of realism causes medically trained GAs to ignore these lifeforms within the virtual world as they lack the necessary operational physiology fidelity to be considered credible. The method taken to incorporate an external high-fidelity physiology model solver, HumMod from HC Simulations, LLC, into a multi-modal mixed-reality simulation environment is detailed. The method developed and employed allows a single high-fidelity and high-speed physiology model solver to compute the necessary physiology results of simulated injuries and their interventions to drive physiologic aspects of a rugged human patient simulator and the motion and behaviors of combat casualty characters in the virtual environment. The entire solution allows for configurable physiology to drive specific simulation platform elements of a multi-modal simulation environment. Lastly, a discussion of the profound need for standards to represent, exchange and interpret physiology data streamed throughout the simulation exercise to support the integration of physiology driven simulation platforms across disparate manufacturers, and provide the necessary physiology dimension to an after action review process that includes simulation-based medical training is presented.