Citation

Lu J, Wang X, Chen L, Sun X, Li R, Zhong W, Fu Y, Yang L, Liu W, Han W. World J. Emerg. Med. 2023; 14(4): 273-279.

Copyright

(Copyright © 2023, World Journal of Emergency Medicine Press)

DOI

10.5847/wjem.j.1920-8642.2023.066

PMID

37425090

PMCID

PMC10323497

Abstract

BACKGROUND: Rapid on-site triage is critical after mass-casualty incidents (MCIs) and other mass injury events. Unmanned aerial vehicles (UAVs) have been used in MCIs to search and rescue wounded individuals, but they mainly depend on the UAV operator's experience. We used UAVs and artificial intelligence (AI) to provide a new technique for the triage of MCIs and more efficient solutions for emergency rescue.

METHODS: This was a preliminary experimental study. We developed an intelligent triage system based on two AI algorithms, namely OpenPose and YOLO. Volunteers were recruited to simulate the MCI scene and triage, combined with UAV and Fifth Generation (5G) Mobile Communication Technology real-time transmission technique, to achieve triage in the simulated MCI scene.

RESULTS: Seven postures were designed and recognized to achieve brief but meaningful triage in MCIs. Eight volunteers participated in the MCI simulation scenario. The results of simulation scenarios showed that the proposed method was feasible in tasks of triage for MCIs.

CONCLUSION: The proposed technique may provide an alternative technique for the triage of MCIs and is an innovative method in emergency rescue.

Language: en

Keywords

Artificial intelligence; Emergency medical service; Fifth Generation Mobile Communication Technology; Mass-casualty incidents; Unmanned aerial vehicle