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Virtual Reality Simulation for Training Paramedics on the Life-saving Intraosseous Insertion Procedure

Agazio Riitano

Virtual Reality Simulation for Training Paramedics on the Life-saving Intraosseous Insertion Procedure.

Rel. Fabrizio Lamberti, Bill Kapralos, Adam Dubrowski. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2023

Abstract:

Although numerous scientific studies have demonstrated the safety and effectiveness of intraosseous (IO) insertion as an alternative method for accessing the central circulatory system when other methods are unsuitable or time-consuming, this procedure remains underutilized in the field of paramedicine. This is partially due to paramedics’ lack of confidence in performing it in inherently complex contexts, such as automobile accidents or sudden medical emergencies where rapid administration of fluids and medications is required. The idea of developing a simulation system that leverages the advantages of virtual reality (VR) arises from the need to overcome the challenges that paramedic trainees face during traditional simulation-based learning, which is costly and resource-inefficient. The main objective of this thesis work is to design and develop an innovative VR simulation aimed at training paramedic trainees and novice healthcare providers to increase their confidence in using the IO insertion. This increased confidence may be crucial for boosting the adoption of the technique in real-life situations. Through a series of iterative phases of co-design, requirement analysis, and testing of usability, user experience, and user engagement, a VR simulation capable of realistically recreating scenarios that paramedics might encounter in the field was developed. One unique aspect of the VR simulation is that it offers the users opportunities to interact with an artificial intelligence (AI) driven virtual assistant and receive additional information that can improve their understanding of the procedure and strengthen their cognitive abilities.

Relatori: Fabrizio Lamberti, Bill Kapralos, Adam Dubrowski
Anno accademico: 2023/24
Tipo di pubblicazione: Elettronica
Numero di pagine: 133
Informazioni aggiuntive: Tesi secretata. Fulltext non presente
Soggetti:
Corso di laurea: Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering)
Classe di laurea: Nuovo ordinamento > Laurea magistrale > LM-32 - INGEGNERIA INFORMATICA
Ente in cotutela: University of Ontario Institute of Technology (CANADA)
Aziende collaboratrici: University of Ontario, Istitute of Tech.
URI: http://webthesis.biblio.polito.it/id/eprint/28627
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