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inward physiological states of children that may serve as key markers of social engagement. Such technologies may not only help characterize qualitative aspects of children’s social engagement, but may potentially also assist with the identification and quantification of developmental delays

physiological states of children that may serve as key markers of social engagement. Such technologies may not only help characterize qualitative aspects of children's social engagement, but may potentially also assist with the identification and quantification of developmental delays [22]. This paper explores whether we can successfully leverage modern biosensors to identify children who have been rated by an adult interactive partner as more or less difficult to engage. In particular, we monitored the electrodermal activity of 51 child-adult dyads during a short naturalistic social interaction (see Figure 1 for an example of interaction), and used Support Vector Machines to automatically differentiate children who were rated as easier versus harder to engage. The paper is organized as follows. We begin by summarizing related research on measuring engagement and the use of physiological information in the context of social engagement. We then outline our procedure for collecting data and rating children's engagement. After explaining how the physiological signals are preprocessed, we describe a variety of features to characterize the child and adult's physiological responses. We then report our main findings in terms of classification performance of combinations of different types of features. We conclude by providing some discussion and highlighting future steps to push forward this line of research.