MS, University of Cincinnati, 2015, Engineering and Applied Science: Computer Science

In recent world, human activity recognition has drawn much attention in the field of human computer interaction. There is a growing demand of activity recognition in different areas of everyday living, such as health-care systems like patient health monitoring, home-based rehabilitation, entertainment, and many more. In this research, we are aiming to use activity recognition theory in health-care system to monitor patient behavior during the waiting time at clinical visits. In today's health-care system, patients wait about 22 minutes on average in doctor's offices, and more than four hours in emergency departments. As wait time increases, patient satisfaction drops. With a growing consumer-mindedness of instant gratification or satisfaction, health care providers or hospitals are looking ways to improve productivity, like shortening each patient's path through the health care system, perhaps, adopting measures such as clinics using kiosks, and not reception desks, speedier check-in for returning patients, and taking measures to funnel visitors to the appropriate part of the clinic or hospital when appointments have been arranged earlier, while providing more attentive face-to-face care to those who are first timers to the system and in need. The purpose of this study is to investigate a computer-based means to obtain useful data on typical human behaviors during visits to clinics. A framework to implement the technology to study human behavior has been proposed by Tao Ma[15] recently. In his four-layer hierarchical framework, computer vision is used to study and understand human behavior through body movements. We explore a second framework developed by Saguna et al. [25] which uses probability theory and statistical learning methods to discover complex activity signatures. Additional modalities of information, such as speech, facial expressions, time-based contextual information can also be incorporated to interpret various human behaviors and elicit the cogn (open full item for complete abstract)

Committee: Chia Han Ph.D. (Committee Chair); William Wee Ph.D. (Committee Member); Xuefu Zhou Ph.D. (Committee Member) Subjects: Computer Science