Medical education interfaces through virtual patients based on qualitative simulation

Abstract

Cardiac emergency is one field in medicine widely studied and very often experienced in reality. Furthermore, simulation and training issues on this field require sensitive and expensive techniques. In the following, we describe the development of a virtual human to be used for training applications in the field of cardiac emergencies. The system integrates Artificial Intelligence (AI) techniques for simulating medical conditions (shock states) with a realistic visual simulation of the patient in a 3D environment representing an emergency room (ER). It uses qualitative simulation of the cardiovascular system to generate clinical syndromes and simulate the consequences of the trainee's therapeutic interventions. The use of knowledge-based simulation provides a strong basis to integrate the behavioral aspects with the graphical appearance of a patient in the virtual ER. This also supports the creation of an emotional atmosphere. We describe how a subset of cardiac physiology can be modeled using the qualitative process theory and discuss knowledge representation issues. We then present results obtained by the proposed system and the benefits that can be derived from the use of a virtual patient in terms of training. Finally, we explore the problem of integrating multiple athophysiological models for various aetiologies of shock states. This approach was demonstrated using medicine students who gained good experience which helped them in understanding and handling better these types of emergencies. © Springer-Verlag Berlin Heidelberg 2007.