C3ARESYS – Simulated Combat Casualty Care Training
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Intro
Accelint is advancing combat casualty care training under a Small Business Innovation Research (SBIR) contract with the Program Executive Office for Simulation, Training, and Instrumentation (PEO STRI). The initiative, known as Combat Casualty Care Augmented Reality Intelligent Training Systems (C3ARESYS), uses augmented reality to enhance realism and responsiveness in medical training, improving warfighter readiness.
Challenge
Simulating battlefield medical conditions presents complex challenges. Traditional training methods rely on static mannequins or moulage that cannot respond dynamically to treatment, limiting trainees' ability to experience realistic injury progression. Wounds may look realistic initially but do not change over the course of treatment. Instructors face additional burdens coordinating scenarios manually, which reduces time available for observing and assessing trainee performance. PEO STRI required a system that could replicate realistic trauma responses, provide interactive training experiences, and ease instructor workload without compromising fidelity.
Solution
C3ARESYS leverages Microsoft HoloLens 2 augmented reality goggles to overlay lifelike virtual injuries onto simulated casualties. The system models both physiological and psychological responses that evolve based on trainee actions.
Core capabilities include:
- Real-time, dynamic injury simulation: Trainees see physiological and psychological effects that change according to their diagnosis and treatment decisions.
- Speech-based interaction: Trainees communicate directly with synthetic casualties for a more realistic engagement.
- Instructor oversight tools: Trainers can monitor performance and provide assessment without manually managing scenarios.
Together, these capabilities deliver a responsive, immersive training environment that strengthens warfighter readiness while reducing instructor workload.
Program Impact
C3ARESYS is under evaluation through the SBIR program to enhance training realism, improve instructional efficiency, and provide immediate feedback to trainees. Beyond training applications, future iterations may support deployed medics with real-time guidance in casualty stabilization and prolonged care, and could help first responders care for patients before they access advanced medical facilities.