2019 I/ITSEC

The Application of Augmented Reality for Immersive TC3 Training (Room 320A)

04 Dec 19
9:30 AM - 10:00 AM

Tracks: Full Schedule, Wednesday Schedule

Military medical personnel are the first responders of the battlefield, where they are tasked with maintaining tactical objectives and making critical decisions for care that may determine if a casualty lives. Having providers engage in realistic Tactical Combat Casualty Care (TC3) scenarios can optimize the leadership, teamwork, tactical, and medical skills required to succeed in the challenging situations they may encounter.  An issue that instructors face when attempting to create engaging TC3 training scenarios is effectively simulating battlefield injuries on the standardized patients imitating casualties. While medical moulage offers a static visual portrayal of a wound, instructors often have to provide supplemental content to the scenario using verbal prompts about the patient’s injuries. The goal of this is to add realism and progress the scenario along, however it can often detract from the scenario and add to the workload of the instructor.  Augmented Reality (AR), especially the recent boom in wearable AR headsets, has the potential to revolutionize how TC3 training happens today. AR can provide a unique mix of immersive simulation within the real environment by overlaying dynamic virtual injuries on simulated patients. The AR field has seen billions of dollars invested for development and deployment of hardware and software, which has been leveraged into many fields (e.g., entertainment).  While AR offers many opportunities for training improvement within the TC3 training, several challenges for integrating these technologies still exist. TC3 scenarios present complex environments for AR tracking and projection due to the many dynamics of the scenario (e.g., sunlight, moving patients, tactile nature of procedures). This paper will describe the research and development of an AR-based TC3 training capability for combat medics. Specifically, this paper will explore the technical challenges encountered during development of the capability and provide identified solutions, both hardware and software, for addressing these limitations.