Systematic review on the effectiveness of augmented reality applications in medical training
By Esther Z. Barsom, Maurits Graafland, Marlies P. Schijven. Surgical Endoscopy, 2016
590 citations recorded by the source corpus.
AbstractBackgroundComputer-based applications are increasingly used to support the training of medical professionals. Augmented reality applications (ARAs) render an interactive virtual layer on top of reality. The use of ARAs is of real interest to medical education because they blend digital elements with the physical learning environment. This will result in new educational opportunities. The aim of this systematic review is to investigate to which extent augmented reality applications are currently used to validly support medical professionals training.MethodsPubMed, Embase, INSPEC and PsychInfo were searched using predefined inclusion criteria for relevant articles up to August 2015. All study types were considered eligible. Articles concerning AR applications used to train or educate medical professionals were evaluated.ResultsTwenty-seven studies were found relevant, describing a total of seven augmented reality applications. Applications were assigned to three different categories. The first category is directed toward laparoscopic surgical training, the second category toward mixed reality training of neurosurgical procedures and the third category toward training echocardiography. Statistical pooling of data could not be performed due to heterogeneity of study designs. Face-, construct- and concurrent validity was proven for two applications directed at laparoscopic training, face- and construct validity for neurosurgical procedures and face-, content- and construct validity in echocardiography training. In the literature, none of the ARAs completed a full validation process for the purpose of use.ConclusionAugmented reality applications that support blended learning in medical training have gained public and scientific interest. In order to be of value, applications must be able to transfer information to the user. Although promising, the literature to date is lacking to support such evidence.
Subfields: Computer Vision and Pattern Recognition, Surgery
View Paper: https://www.semanticscholar.org/paper/f42da30f532b4e523630df3206a220d75b35bf85
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- L. Lanfermann
- T. Bärnighausen
- S. Barteit
- F. Neuhann
- C. Beiersmann
Citations in the corpus
- A Survey on Mobile Augmented Reality With 5G Mobile Edge Computing: Architectures, Applications, and Technical Aspects (2021, unknown): “AR based medical training [157], AR/VR based rehabilitation [158], MAR based personalized medicine enhanced with eye tracing [159], speech recognition, motion tracking are few other applications of MAR in healthcare.”
- Augmented, Mixed, and Virtual Reality-Based Head-Mounted Devices for Medical Education: Systematic Review (2021, background): “Currently, there is a lack of insights on HMDs particularly in LMICs, as most reviews on HMDs have focused on high-income countries, on AR for medical education, or on AR and VR but not in the context of health [16-20].”
- Digital Twin: Values, Challenges and Enablers From a Modeling Perspective (2019, unknown): “[515] E.”