Meta-patients: Using Mixed Reality Patients and an AI Framework for Simulating Life-Like Clinical Examinations.

Rob Burton, Gary Grant, Eileen Grafton, Daniel Della-Bosca, Louise Humphreys

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

3 Citations (Scopus)

Abstract

This chapter addresses an augmented learning experience created for the Griffith University School of Nursing and Midwifery in 2022. An interdisciplinary research team from Griffith University (Australia) deployed the first iteration of an application for students in response to the difficulties imposed through the previous two years. The impacts of the COVID pandemic bought challenges to the Bachelor of Nursing program, particularly in relation to student competency in the physical assessment of patients, through objective structured clinical examinations. This pilot study introduced life-like, simulated patients, designed and rendered within Unreal Engine to the students. The patients were accessible through cross platform applications, including mixed reality devices. Students were also able to interact with patient information communicated using the AI framework afforded by Microsoft PowerApps all packaged in a bespoke SharePoint site. Student participants were interviewed as part of the development process and approved of Augmented and Mixed Reality as successful platforms for the deployment of the simulated patient scenarios within Microsoft Teams and available through a mobile application and mixed reality device.
Original languageEnglish
Title of host publicationAugmented Reality and Artificial Intelligence.
Subtitle of host publicationThe Fusion of Advanced Technologies
EditorsVladimir Geroimenko
Place of PublicationSwitzerland
PublisherSpringer
Pages193-210
Number of pages18
Edition1st
ISBN (Electronic)9783031271663
ISBN (Print)9783031271656, 9783031271687
DOIs
Publication statusPublished - 30 Apr 2023

Publication series

NameSpringer Series on Cultural Computing
PublisherSpringer
ISSN (Print)2195-9056
ISSN (Electronic)2195-9064

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