An Improved Framework to Assess the Evaluation of Extended Reality Healthcare Simulators using Machine Learning

Avinash Gupta, Harris Nisar

Abstract: In this paper, an improved machine learning framework for the assessment of Extended Reality (XR) based simulators is presented. The simulators in focus are healthcare simulators development for training and education of medical residents and students. Machine learning (ML) has been used by many researchers to assess medical simulators. However, there is a lack of standard when conducting such an assessment. Some researchers have also investigated the standardization of the assessment process using ML, but they are limited to virtual reality. In this paper, the objective is to develop an improved Framework encompassing assessment processes for Virtual, Mixed and Augmented Reality based simulators and various ML models.