Abstract
Social engagement is a key indicator of an individual's socio-emotional and cognitive states. For a child with Autism Spectrum Disorder (ASD), this serves as an important factor in assessing the quality of the interactions and interventions. So far, qualitative measures of social engagement have been used extensively in research and in practice, but a reliable, objective, and quantitative measure is yet to be widely accepted and utilized. In this paper, we present our work on the development of a framework for the automated measurement of social engagement in children with ASD that can be utilized in real-world settings for the long-term clinical monitoring of a child's social behaviors as well as for the evaluation of the intervention methods being used. We present a computational modeling approach to derive the social engagement metric based on a user study with children between the ages of 4 and 12 years. The study was conducted within a child-robot interaction setting that targets sensory processing skills in children. We collected video, audio and motion-tracking data from the subjects and used them to generate personalized models of social engagement by training a multi-channel and multi-layer convolutional neural network. We then evaluated the performance of this network by comparing it with traditional classifiers and assessed its limitations, followed by discussions on the next steps toward finding a comprehensive and accurate metric for social engagement in ASD.
Highlights
Social engagement of a child is an indicator of his/her socioemotional and cognitive states
This paper presents our first step toward an automated quantifiable measure of social engagement derived from behavioral data collected from two groups of children, one typically developing (TD) and one with Autism Spectrum Disorder (ASD)
The performance remains steady with an average accuracy of 0.7767 for the ASD group and 0.7918 for the TD group
Summary
Social engagement of a child is an indicator of his/her socioemotional and cognitive states. Automated Social Engagement Measure in ASD quantification of engagement is still limited but can allow for an objective interpretation of engagement and the contributing target behaviors, and help to identify methods to improve engagement in different settings, especially when targeting a specific health condition It serves both as an outcome measure and as an objective measure of the quality of an activity, interaction, or intervention (Kishida and Kemp, 2006). ASD is a neurodevelopmental disorder that causes significant impairment in three broad areas of functioning: communication, social interaction, and restricted and repetitive behaviors (American Psychiatric Association., 2013) This means that children interact with their peers infrequently, preventing the formation of lasting and meaningful social relationships and resulting in social withdrawal. These children often feel isolated from or rejected by peers and are more likely to develop behavioral problems (Ollendick et al, 1992) as well as anxiety and depression (Tantam, 2000; Bellini, 2006)
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