Smart robopatients: Evolving the designs of virtual reality-based patient simulators for clinical training

A novel framework was developed to create a self-learning smart robopatient for clinical training that adapts its morphology and behavior with time, based on field data from clinical cases. A set of three functional modalities of the robopatient, viz.: patient assessment, monitoring and treatment, are available within a virtual reality (VR) environment. The entities within each modality are dynamically updated based on automated analysis of patient-doctor/nurse interaction data available as videos, prescriptions, notes, etc., creating a robust process flow for improving the design of the VR-based patient simulator with time. This, in turn, enables continually improved training of medical professionals.