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by Sergio Ernesto Garcia
Institution: | Georgia Tech |
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Year: | 2017 |
Keywords: | technological rehabilitation; cerebral palsy; Super Pop VR[TM]; pattern recognition; upper-body physiotherapy; reaching kinematics; kinematic behavior; instance- and individual-based classification approaches |
Posted: | 02/01/2018 |
Record ID: | 2164759 |
Full text PDF: | http://hdl.handle.net/1853/58230 |
In the physical therapy and rehabilitation field, virtual reality serious gaming systems have been developed to address the problem of non-compliance to perform the recommended in-home exercises, which limits greater improvement due to interrupted training. However, existing systems do not fully mimic the interactions between patients and their therapists, since they do not employ assessment of the user's kinematic performance, nor do they provide targeted corrective feedback. As such, the purpose of this dissertation is to fill in the gap by designing, developing, and validating a more robust system that, not only increases users' motivation to comply with their intervention protocols, but also provides the necessary targeted corrective feedback as a function of the objective assessment of the user's kinematic performance. This dissertation presents data to support the claim that our system is a feasible and effective approach for inducing changes in users' kinematic behavior in real-time, thus allowing for the potential to serve as part of various physiotherapy protocols for individuals who have some form of motor skills disorder.Advisors/Committee Members: Howard, Ayanna M (advisor), Vela, Patricio A (committee member), Bhatti, Pamela T (committee member), Ames, Aaron D (committee member), Chen, Yu-Ping (committee member).
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