Automated Unmanned Aerial System for Camera-Based Semi-Automatic Triage Categorization in Mass Casualty Incidents

Drones, vol. 8, pp. 589

Abstract

Using drones to obtain vital signs during mass-casualty incidents can be extremely helpful for first responders. Thanks to technological advancements, vital parameters can now be remotely assessed rapidly and robustly. This motivates the development of an automated unmanned aerial system (UAS) for patient triage, combining methods for the automated detection of respiratory-related movements and automatic classification of body movements and body poses with an already published algorithm for drone-based heart rate estimation. A novel UAS-based triage algorithm using UAS-assessed vital parameters is proposed alongside a robust UAS-based respiratory rate assessment and pose classification algorithm. A pilot concept study involving 15 subjects and 30 vital sign measurements under outdoor conditions shows that with our approach, an overall triage classification accuracy of 89% and an F1 score of 0.94 can be achieved, demonstrating its basic feasibility.

Authors 8

1. Lucas Mösch corresponding Aachen Department of Anesthesiology Faculty of Medicine

   RWTH Aachen University

   Affiliation as printed

   Department of Anesthesiology, Faculty of Medicine, RWTH Aachen University, 52074 Aachen, Germany

2. Diana Queirós Pokee Aachen Department of Anesthesiology Faculty of Medicine

   RWTH Aachen University

   Affiliation as printed

   Department of Anesthesiology, Faculty of Medicine, RWTH Aachen University, 52074 Aachen, Germany

3. Isabelle Barz Aachen Institute of Flight System Dynamics

   RWTH Aachen University

   Affiliation as printed

   Institute of Flight System Dynamics, RWTH Aachen University, 52062 Aachen, Germany

4. Anna Müller Aachen Department of Anesthesiology Faculty of Medicine

   RWTH Aachen University

   Affiliation as printed

   Department of Anesthesiology, Faculty of Medicine, RWTH Aachen University, 52074 Aachen, Germany

5. Andreas Follmann Aachen Department of Anesthesiology Faculty of Medicine

   RWTH Aachen University

   Affiliation as printed

   Department of Anesthesiology, Faculty of Medicine, RWTH Aachen University, 52074 Aachen, Germany

6. Dieter Moormann Aachen Institute of Flight System Dynamics

   RWTH Aachen University

   Affiliation as printed

   Institute of Flight System Dynamics, RWTH Aachen University, 52062 Aachen, Germany

7. Michael Czaplik Aachen Department of Anesthesiology Faculty of Medicine

   RWTH Aachen University

   Affiliation as printed

   Department of Anesthesiology, Faculty of Medicine, RWTH Aachen University, 52074 Aachen, Germany

8. Carina Barbosa Pereira Aachen Department of Anesthesiology Faculty of Medicine

   RWTH Aachen University

   Affiliation as printed

   Department of Anesthesiology, Faculty of Medicine, RWTH Aachen University, 52074 Aachen, Germany