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A Person-Centric Design Framework for At-Home Motor Learning in Serious Games

Abstract In motor learning, real-time multi-modal feedback is a critical element in guided training. Serious games have been introduced as a platform for at-home motor training due to their highly interactive and multi-modal nature. This dissertation explores the design of a multimodal environment for at-home training in which an autonomous system observes and guides the user in the place of a live trainer, providing real-time assessment, feedback and difficulty adaptation as the subject masters a motor skill. After an in-depth review of the latest solutions in this field, this dissertation proposes a person-centric approach to the design of this environment, in contrast to the standard techniques implemented in related work, to address many of the ... (more)
Created Date 2017
Contributor Tadayon, Ramin (Author) / Panchanathan, Sethuraman (Advisor) / McDaniel, Troy (Committee member) / Amresh, Ashish (Committee member) / Glenberg, Arthur (Committee member) / Li, Baoxin (Committee member) / Arizona State University (Publisher)
Subject Computer science
Type Doctoral Dissertation
Extent 222 pages
Language English
Reuse Permissions All Rights Reserved
Note Doctoral Dissertation Computer Science 2017
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis