Project description
Mixed reality to train abilities for first medical support
The role of medical first responders (MFRs) in mass casualty incidents like natural disasters and attacks on public transportation is crucial today. The capabilities of MFRs are essential since they are first on the scene to provide life-saving assistance to victims. But there are critical training gaps that need to be filled. In this context, the EU-funded MED1stMR project will provide a new generation of mixed reality training by adapting haptic feedback and enabling mixed reality to prepare MFRs for disasters. It will provide flexibility for adapting to trainee needs manually or by applying AI-driven smart scenarios.
Objective
Mass-casualty incidents with injured persons caused by human-made or by natural disasters are increasing globally. In such situations, medical first responders (MFR) need to perform basic life support and first aid to help stabilize victims until arrival of further support. Proper evaluation of situations, checking and monitoring the vital states, and choosing the most appropriate strategy for proceeding with treatments are challenges. However, current training abilities for such scenarios are limited.
The MED1stMR consortium has identified Mixed Reality (MR) training as opportunity to better train and prepare MFRs for disasters. Thus, MED1stMR will develop a new generation of MR training providing haptic feedback through the integration of high-fidelity patient simulation manikins into MR. Thereby, MED1stMR offers a much richer sensory experience bringing MR training closer to reality. To enhance the effectiveness of MR training a physiological signal and trainee behavior feedback loop will be integrated for scenario control. In this respect, wearable technologies with body sensors will be developed allowing to monitor states and behaviour of MFR during training. Together with a model for effective performance in medical emergencies (EPME) this data will enable adapting training to trainee needs, manually or by artificial intelligence driven smart scenarios. Partnering MFR will be included in the project developments by an Agile End User Centred Research Methodology.
To this end, MED1stMR will pursue the following pioneering objectives: a) Developing a pioneering MR training approach for enhanced realism, b) Developing effective training scenarios and a training curriculum through user-centred design with cross-sectoral MFR, c) Realisation of a physiological signal and trainee behaviour feedback loop and EPME model for smart scenario control thereby enhancing effectiveness of MR training and d) To position the pioneering MR training approach across Europe
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. This project's classification has been validated by the project's team.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. This project's classification has been validated by the project's team.
- natural sciencescomputer and information sciencesartificial intelligence
- natural sciencescomputer and information sciencesinternetinternet of things
- medical and health sciencesclinical medicineemergency medicine
- social sciencessociologygovernancecrisis management
- natural sciencesearth and related environmental sciencesphysical geographynatural disasters
Programme(s)
Call for proposal
(opens in new window) H2020-SU-SEC-2018-2019-2020
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H2020-SU-SEC-2020
Funding Scheme
RIA - Research and Innovation actionCoordinator
1210 Wien
Austria
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Participants (20)
69117 Heidelberg
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901 87 Umea
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3012 Bern
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8700 Leoben
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8807 Freienbach
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
1050-059 Lisboa
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
6836 BA Arnhem
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
41300 La Rinconada
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1040 WIEN
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
8010 Graz
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
Participation ended
8790 Eisenerz
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542 48 THESSALONIKI
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1210 Wien
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28046 MADRID
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Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
28003 Madrid
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69120 Heidelberg
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831 27 Ostersund
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1000 Bruxelles / Brussel
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2520 Emblem Ranst
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78120 Furtwangen
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