Ph.D. Dissertation Proposal Defense "A Virtual Doctor for Quick Response to People at Need" By Stavros Mallios

Ph.D. Committee:  Drs. Nikolaos Bourbakis (advisor), Soon Chung, Yong Pei, and Larry Lawhorne (Geriatrics)

ABSTRACT:

The increasing occurrence of chronic conditions among the ageing population and people at risk is one of the major challenges for our society and the excessive costs for its healthcare systems. Prevention, early detection and efficient management of chronic, long-term conditions contribute radically to the individual wellbeing and the economic sustainability of social and healthcare systems. 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.

The 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”.

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 a dialogue system that is modeled with Stochastic Petri Nets. Therefore, the goal of such a system is health monitoring, quick diagnosis, real-time response to critical situations and, generally, the life improvement for certain categories of people at need.