The recent emergence of comfortable wearable sensors has focused almost entirely on monitoring physical activity, ignoring opportunities to monitor more subtle phenomena, such as the quality of social interactions. We argue that it is compelling to address whether physiological sensors can shed light on quality of social interactive behavior. This work leverages the use of a wearable electrodermal activity (EDA) sensor to recognize ease of engagement of children during a social interaction with an adult. In particular, we monitored 51 child-adult dyads in a semistructured play interaction and used Support Vector Machines to automatically identify children who had been rated by the adult as more or less difficult to engage. We report on the classification value of several features extracted from the child's EDA responses, as well as several other features capturing the physiological synchrony between the child and the adult.
Hernandez et al. REF used wearable electrodermal activity sensors to detect the engagement of children during social interactions with adults.
Using electrodermal activity to recognize ease of engagement in children during social interactions
Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing
Computer Science