An Affect-Sensitive Social Interaction Paradigm Utilizing Virtual Reality Environments for Autism Intervention

Authors:
Karla Conn Welch;Uttama Lahiri;Changchun Liu;Rebecca Weller;Nilanjan Sarkar;Zachary Warren
Affiliations:
Department of Electrical Engineering and Computer Science,;Department of Mechanical Engineering,;Department of Electrical Engineering and Computer Science,;Department of Mechanical Engineering,;Department of Mechanical Engineering, and Department of Electrical Engineering and Computer Science,;Vanderbilt Kennedy Center and Department of Pediatrics, Vanderbilt University, Nashville, TN 37212
Venue:
Proceedings of the 13th International Conference on Human-Computer Interaction. Part III: Ubiquitous and Intelligent Interaction
Year:
2009

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Abstract

This paper describes the design and development of both software to create social interaction modules on a virtual reality (VR) platform and individualized affective models for affect recognition of children with autism spectrum disorders (ASD), which includes developing tasks for affect elicitation and using machine-learning mathematical tools for reliable affect recognition. A VR system will be formulated that can present realistic social communication tasks to the children with ASD and can monitor their affective response using physiological signals, such as cardiovascular activities including electrocardiogram, impedance cardiogram, photoplethysmogram, and phonocardiogram; electrodermal activities including tonic and phasic responses from galvanic skin response; electromyogram activities from corrugator supercilii, zygomaticus major, and upper trapezius muscles; and peripheral temperature. This affect-sensitive system will be capable of systematically manipulating aspects of social communication to more fully understand its salient components for children with ASD.