Hidden Markov Models For Learning Evaluation In Virtual-Reality Simulators

Abstract Training on simulator systems based on virtual reality (VR) for learning or learning improvement may be a cost-effective and efficient alternative to traditional training methods. A new approach for online or Web-based evaluation of training performed in simulators based on VR is proposed. This approach uses hidden Markov models for modelling and classification of training in pre-defined classes of training. In this article we show an example of application in a simulator of bone marrow harvest for transplant.

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