Graduation Semester and Year
2018
Language
English
Document Type
Dissertation
Degree Name
Doctor of Philosophy in Computer Science
Department
Computer Science and Engineering
First Advisor
Vassilis Athitsos
Abstract
Cognitive impairments in early childhood can lead to poor academic performance and require proper remedial intervention at the appropriate time. ADHD a?ects about 6-7% of children and is a psychiatric neurodevelopmental disorder that is very hard to diagnose or tell apart from other disorders. Cognitive insu?ciencies hinder the development of working memory and can a?ect school success and even have long term e?ects that can result in low self-esteem and self-acceptance. The main aim of this research is to investigate development of an automated and non-intrusive system for assessing physical exercises related to the treatment and diagnosis of Attention De?cit Hyperactivity Disorder (ADHD). A proposed arti?cial intelligent cognitive behavior assessment system takes advantage of state-of-the-art knowledge from both ?elds of Computer and Cognitive sciences, and aims to assist therapists in decision making, by providing advanced statistics and sophisticated metrics regarding the subject’s performance. The ultimate goal is to deliver meaningful information to cognitive experts and help develop skills in children that can result in overall improvement of child’s academic performance. To facilitate this, research has been employed in arti?cial intelligence, computer vision, machine learning and human computer interaction. Computational methods for human motion analysis are proposed in this dissertation; to provide automatic measurements of various metrics of performance. These are metrics related to generic motion features as well as metrics explicitly de?ned by experts. To conclude, a novel set of user-interfaces is introduced, speci?cally designed to assist human experts with data-capturing and motion-analysis, using intuitive and descriptive visualizations.
Keywords
Computer vision, Deep learning, Artificial intelligence
Disciplines
Computer Sciences | Physical Sciences and Mathematics
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Gattupalli, Srujana, "Artificial Intelligence For Cognitive Behavior Assessment In Children" (2018). Computer Science and Engineering Dissertations. 266.
https://mavmatrix.uta.edu/cse_dissertations/266
Comments
Degree granted by The University of Texas at Arlington