Date Available
11-2-2018
Year of Publication
2018
Degree Name
Doctor of Philosophy (PhD)
Document Type
Doctoral Dissertation
College
Engineering
Department/School/Program
Electrical and Computer Engineering
First Advisor
Dr. Sen-Ching S. Cheung
Abstract
This dissertation investigates the development and use of self-images in augmented reality systems for learning and learning-based activities. This work focuses on self- modeling, a particular form of learning, actively employed in various settings for therapy or teaching. In particular, this work aims to develop novel multimedia systems to support the display and rendering of augmented self-images. It aims to use interactivity (via games) as a means of obtaining imagery for use in creating augmented self-images. Two multimedia systems are developed, discussed and analyzed. The proposed systems are validated in terms of their technical innovation and their clinical efficacy in delivering behavioral interventions for young children on the autism spectrum.
Digital Object Identifier (DOI)
https://doi.org/10.13023/etd.2018.424
Funding Information
This research was supported by National Science Foundation under Grant No. 1237134.
This research was supported by funding from the Halcomb Fellowship in Medicine and Engineering, 2015-2016.
Recommended Citation
Uzuegbunam, Nkiruka M. A., "SELF-IMAGE MULTIMEDIA TECHNOLOGIES FOR FEEDFORWARD OBSERVATIONAL LEARNING" (2018). Theses and Dissertations--Electrical and Computer Engineering. 124.
https://uknowledge.uky.edu/ece_etds/124
Included in
Biomedical Commons, Engineering Education Commons, Graphics and Human Computer Interfaces Commons, Signal Processing Commons
