Document Type

Conference Proceeding



Format of Original

6 p.

Publication Date



Institute of Electrical and Electronics Engineers (IEEE)

Source Publication

Conference on Computers, Software, and Applications (COMPSAC)

Original Item ID

doi: 10.1109/COMPSAC.2013.109


The emergent prevalence of childhood and adolescent obesity remains one of the most significant health care challenges facing the United States today. On the other hand, breakthroughs in Human-Robot Interaction (HRI) research and the diminishing cost of personal robots and virtual agents along with the ever-increasing use of smart personal devices, suggests that there is room for harnessing the power of ubiquitous intelligent systems that can work in partnership to solve some of our most difficult challenges in the very near future. In this paper, we present the design and prototype implementation of a collective intelligence approach aimed at employing machine learning algorithms that work in concert to facilitate the personalization of a humanoid robot Health Coach with a focus on childhood obesity intervention through Child-Robot Interactions and other adaptive Ubiquitous Computing (UbiComp) solutions.


Accepted version. Published as part of the conference, Conference on Computers, Software, and Applications (COMPSAC), 2013: 690-695. DOI. © 2013 Institute of Electrical and Electronics Engineers. Used with permission.

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