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© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Simulation-based medical training is considered an effective tool to acquire/refine technical skills, mitigating the ethical issues of Halsted’s model. This review aims at evaluating the literature on medical simulation techniques based on augmented reality (AR), mixed reality (MR), and hybrid approaches. The research identified 23 articles that meet the inclusion criteria: 43% combine two approaches (MR and hybrid), 22% combine all three, 26% employ only the hybrid approach, and 9% apply only the MR approach. Among the studies reviewed, 22% use commercial simulators, whereas 78% describe custom-made simulators. Each simulator is classified according to its target clinical application: training of surgical tasks (e.g., specific tasks for training in neurosurgery, abdominal surgery, orthopedic surgery, dental surgery, otorhinolaryngological surgery, or also generic tasks such as palpation) and education in medicine (e.g., anatomy learning). Additionally, the review assesses the complexity, reusability, and realism of the physical replicas, as well as the portability of the simulators. Finally, we describe whether and how the simulators have been validated. The review highlights that most of the studies do not have a significant sample size and that they include only a feasibility assessment and preliminary validation; thus, further research is needed to validate existing simulators and to verify whether improvements in performance on a simulated scenario translate into improved performance on real patients.

Details

Title
Augmented Reality, Mixed Reality, and Hybrid Approach in Healthcare Simulation: A Systematic Review
Author
Viglialoro, Rosanna Maria 1 ; Condino, Sara 2   VIAFID ORCID Logo  ; Turini, Giuseppe 3   VIAFID ORCID Logo  ; Carbone, Marina 2   VIAFID ORCID Logo  ; Ferrari, Vincenzo 2 ; Gesi, Marco 4 

 EndoCAS Center, Department of Translational Research and of New Surgical and Medical Technologies, University of Pisa, 56124 Pisa, Italy; [email protected] (G.T.); [email protected] (M.C.); [email protected] (V.F.) 
 EndoCAS Center, Department of Translational Research and of New Surgical and Medical Technologies, University of Pisa, 56124 Pisa, Italy; [email protected] (G.T.); [email protected] (M.C.); [email protected] (V.F.); Dipartimento di Ingegneria dell’Informazione, University of Pisa, 56122 Pisa, Italy 
 EndoCAS Center, Department of Translational Research and of New Surgical and Medical Technologies, University of Pisa, 56124 Pisa, Italy; [email protected] (G.T.); [email protected] (M.C.); [email protected] (V.F.); Computer Science Department, Kettering University, Flint, MI 48504, USA 
 Department of Translational Research and of New Surgical and Medical Technologies, University of Pisa, 56126 Pisa, Italy; [email protected]; Center for Rehabilitative Medicine “Sport and Anatomy”, University of Pisa, 56121 Pisa, Italy 
First page
2338
Publication year
2021
Publication date
2021
Publisher
MDPI AG
e-ISSN
20763417
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2534646669
Copyright
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.