Publication Date


Document Type


Committee Members

Nikolaos Bourbakis (Advisor), Soon Chung (Committee Member), Larry Lawhorne (Committee Member), Yong Pei (Committee Member)

Degree Name

Doctor of Philosophy (PhD)


One of the challenges of our society is the existence of chronic-related conditions and diseases among the elderly and people at risk. Apart from the welfare of people, a significant impact of this phenomenon is the accumulation of high financial costs for both individuals and health care systems. In order to address this issue and to reduce its effects, many efforts have been made towards preventing, identifying in early stages and, generally, managing chronic-related medical conditions and diseases. As a result, there has been a keen research and market interest in health monitoring devices during the past few decades. Nevertheless, despite the progress in the field of health monitoring, these devices are still unable to measure certain symptoms with sensors. A feasible solution to the aforementioned problem comes from the area of human-machine interaction. However, although human-machine interaction devices have advanced recently, they are still far from replacing the human from the interaction loop. Their major drawback is that they cannot reliably and efficiently respond to human requests, since they mainly behave as "answering machines". Moreover, the majority of these systems fail to take certain human factors, such as one's emotional condition, into consideration. In response to this need, we propose a Virtual Doctor system that is able to measure a patient's pathological data and also competently extract their non-measurable symptoms by incorporating an intelligent human-computer dialogue system that is modeled with Stochastic Petri Nets. In addition to this, the dialogue system will also be able to take human communication factors, such as the patient's emotional condition, as well as other resources, such as their medical history, into account. Therefore, the ultimate goal of the general system is health monitoring, quick and reliable prognosis of a human's health condition, real-time response to critical situations and, generally, the life improvement for certain categories of people in need.

Page Count


Department or Program

Department of Computer Science and Engineering

Year Degree Awarded