Real-Time Automated Patient Identification and Documentation - TC3 (RAPID-TC3)

The limited medics available on the battlefield are tasked not only with treating all patients but also with documenting each patient's injuries and care. This proposal presents RAPID-TC3 to assist medics by using artificial intelligence (AI) to automate tactical combat casualty care (TC3) reporting. RAPID-TC3 consists of a headset-mounted camera that is robust to challenging battlefield conditions, including bright/low-lighting and diverse weather conditions. RAPID-TC3 uses COTS stereo cameras to process the scene and generate its 3D representation. We detect all casualties, medical equipment, and medical procedures performed by the medic on each patient. Using depth from stereo, we create 3D skeletons, body part segments, and body shapes for each casualty. We track and re-identify each casualty as the patients and medics move throughout the scene. Per-module updates are done with varying frequency, to balance accuracy and computational efficiency. By mapping the detected medical devices and interventions to each patient's body, we are able to generate TC3 report data for each casualty. Our system can run for 2 hours, and all computing is done on the edge.