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

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

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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 Bike Parts - E-Bike Parts 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 Boys Shorts 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.