Anxiety Meter for Children with ASD: Classifier Development and User Interface Usability Study
Year: 2015
Type: dissertation
Abstract: Communication deficits and difficulties with introspection and emotional awareness in autism spectrum disorder (ASD) are key barriers to effective treatment of comorbid anxiety. This thesis contributes to reducing these barriers by adding to the body of evidence supporting the use of a physiological, language-free approach for improving awareness and management of anxiety in ASD. First, I demonstrate the specificity of physiological patterns to anxiety-related arousal by examining automatic classification techniques for differentiation of anxiety-related arousal from arousal related to other cognitive and physical processes. Achieving over 80% classification accuracy support the feasibility of using physiological markers of anxiety outside controlled laboratory settings. The second contribution was to investigate the usability of a visual interface for promoting awareness of physiological anxiety symptoms in children with ASD. To this end, I identified usability issues related to attention and provided recommendations to improve the usability of this approach for children with ASD.
Source: TSpace (University of Toronto)
Authors: Hoi-Yun Chiu, Tabitha Anne
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
Funder: Government of Ontario
OpenAlex ID: W2767499425