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Goal-seeking Decision Support System to Empower Personal Wellness Management

Chippa, Mukesh K
http://rave.ohiolink.edu/etdc/view?acc_num=akron1480413936639467

Abstract Details

2016, Doctor of Philosophy, University of Akron, Computer Engineering.
Obesity has reached epidemic proportions globally, with more than one billion adults overweight with at least three hundred million of them clinically obese; this is a major contributor to the global burden of chronic disease and disability. This can also be associated with the rising health care costs; in the USA more than 75\% of health care costs relate to chronic conditions such as Diabetes and Hypertension. While there are various technological advancements in fitness tracking devices such as Fitbit, and many employers offer wellness programs, such programs and devices have not been able to create societal scale transformations in the life style of the users. The challenge in keeping healthy people healthy and helping them to be intrinsically motivated to manage their own health is at the focus for this investigation on Personal Wellness Management. In this dissertation, this problem is presented as a decision making under uncertainty where the participant takes an action at discrete time steps and the outcome of the action is uncertain. The main focus is to formulate the decision making problem in the Goal-seeking framework. To evaluate this formulation, the problem was also formulated in two classical sequential decision-making frameworks --- Markov Decision Process and Partially Observable Markov Decision Process. The sequential decision-making frameworks allow us to compute optimal policies to guide the participants' choice of actions. One of the major challenges in formulating the wellness management problem in these frameworks is the need for clinically validated data. While it is unrealistic to find such experimentally validated data, it is also not clear that the models in fact capture all the inconstraints that are necessary to make the optimal solutions effective for the participant. The Goal-seeking framework offers an alternative approach that does not require explicit modeling of the participant or the environment. This dissertation presents a software system that is designed in the Goal-seeking framework. The architecture of the system is extensible. A modular subsystem that is useful to visualize exercise performance data that are gathered from a Kinect camera is described.
Shivakumar Sastry, Dr (Advisor)
Nghi Tran, Dr (Committee Member)
Igor Tsukerman, Dr (Committee Member)
William Schneider IV, Dr (Committee Member)
Victor Pinheiro, Dr (Committee Member)
120 p.
Computer Engineering
decision support system, personalized wellness management, Goal seeking paradigm, markov decision process, partially observable markov decision process

Recommended Citations

Citations

  • Chippa, M. K. (2016). Goal-seeking Decision Support System to Empower Personal Wellness Management [Doctoral dissertation, University of Akron]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=akron1480413936639467

    APA Style (7th edition)

  • Chippa, Mukesh. Goal-seeking Decision Support System to Empower Personal Wellness Management. 2016. University of Akron, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=akron1480413936639467.

    MLA Style (8th edition)

  • Chippa, Mukesh. "Goal-seeking Decision Support System to Empower Personal Wellness Management." Doctoral dissertation, University of Akron, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=akron1480413936639467

    Chicago Manual of Style (17th edition)

akron1480413936639467
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© 2016, all rights reserved.
This open access ETD is published by University of Akron and OhioLINK.