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The Effect of Holographic Heart Models and Mixed Reality for Anatomy Learning in Congenital Heart Disease: An Exploratory Study

Authors :
d'Aiello A. F.
Cabitza F.
Natali C.
Vigano S.
Ferrero P.
Bognoni L.
Pasqualin G.
Giamberti A.
Chessa M.
D'Aiello, A
Cabitza, F
Natali, C
Vigano, S
Ferrero, P
Bognoni, L
Pasqualin, G
Giamberti, A
Chessa, M
Source :
Journal of Medical Systems. 47
Publication Year :
2023
Publisher :
Springer Science and Business Media LLC, 2023.

Abstract

In this paper, we present an exploratory study on the potential impact of holographic heart models and mixed reality technology on medical training, and in particular in teaching complex Congenital Heart Diseases (CHD) to medical students. Fifty-nine medical students were randomly allocated into three groups. Each participant in each group received a 30-minute lecture on a CHD condition interpretation and transcatheter treatment with different instructional tools. The participants of the first group attended a lecture in which traditional slides were projected onto a flat screen (group “regular slideware”, RS). The second group was shown slides incorporating videos of holographic anatomical models (group “holographic videos”, HV). Finally, those in the third group wore immersive, head-mounted devices (HMD) to interact directly with holographic anatomical models (group “augmented reality”, AR). At the end of the lecture, the members of each group were asked to fill in a multiple-choice questionnaire aimed at evaluating their topic proficiency, as a proxy to evaluate the effectiveness of the training session (in terms of acquired notions); participants from group AR were also asked to fill in a questionnaire regarding the recommendability and usability of the MS Hololens HMDs, as a proxy of satisfaction regarding its use experience (UX). The findings show promising results for usability and user acceptance.

Details

ISSN :
1573689X
Volume :
47
Database :
OpenAIRE
Journal :
Journal of Medical Systems
Accession number :
edsair.doi.dedup.....eb76b95731d81c4359638f86cffb0a1d