NextGen Training for Medical First Responders: Advancing Mass-Casualty Incident Preparedness through Mixed Reality Technology

Author:

Zechner Olivia12ORCID,García Guirao Daniel3ORCID,Schrom-Feiertag Helmut1ORCID,Regal Georg1ORCID,Uhl Jakob Carl12ORCID,Gyllencreutz Lina4ORCID,Sjöberg David5ORCID,Tscheligi Manfred2ORCID

Affiliation:

1. Center for Technology Experience, Austrian Institute of Technology, 1210 Vienna, Austria

2. Department for Artificial Intelligence and Human Interfaces, University of Salzburg, 5020 Salzburg, Austria

3. Energy & Industry 5.0 Division, IDENER, 41300 Sevilla, Spain

4. Department of Nursing & Department of Surgical and Perioperative Sciences, Umeå University, 901 87 Umeå, Sweden

5. Police Education Unit, Umeå University, 901 87 Umeå, Sweden

Abstract

Mixed reality (MR) technology has the potential to enhance the disaster preparedness of medical first responders in mass-casualty incidents through new training methods. In this manuscript, we present an MR training solution based on requirements collected from experienced medical first responders and technical experts, regular end-user feedback received through the iterative design process used to develop a prototype and feedback from two initial field trials. We discuss key features essential for an effective MR training system, including flexible scenario design, added realism through patient simulator manikins and objective performance assessment. Current technological challenges such as the responsiveness of avatars and the complexity of smart scenario control are also addressed, along with the future potential for integrating artificial intelligence. Furthermore, an advanced analytics and statistics tool that incorporates complex data integration, machine learning for data analysis and visualization techniques for performance evaluation is presented.

Funder

European Union’s Horizon 2020 Research and Innovation Programme

Publisher

MDPI AG

Subject

Computer Networks and Communications,Computer Science Applications,Human-Computer Interaction,Neuroscience (miscellaneous)

Reference37 articles.

1. Commission, E. (2021). Overview of Natural and Man-Made Disaster Risks the European Union May Face, Publications Office of the European Union. Technical Report.

2. Feyen, L., Ciscar, J., Gosling, S., Ibarreta, D., and Soria, A. (2020). Climate Change Impacts and Adaptation in Europe: JRC PESETA IV Final Report, Publications Office of the European Union. Technical Report 30180.

3. Europol (2021). European Union Terrorism Situation and Trend Report, Publications Office of the European Union. Technical Report.

4. Live-action mass-casualty training and virtual world training: A comparison;Shubeck;Proc. Hum. Factors Ergon. Soc. Annu. Meet.,2016

5. Preparing medical first responders for crises: A systematic literature review of disaster training programs and their effectiveness;Baetzner;Scand. J. Trauma, Resusc. Emerg. Med.,2022

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3