Machine Learning to Assess Child Attachment
A computer programme that uses machine learning and smart sensors were found to accurately assess attachment in children. The School Attachment Monitor (SAM) developed by University of Glasgow is delivered by novel software which interacts with child participants, starting with warm-up activities to familiarise them with the task. Children are invited to play with ‘smart dolls’ while interacting with a story on the computer, and data on their attachment patterns are captured through video recording and movement sensors in the smart dolls. Insecure attachment is associated with increased risk of pyschopathology of various types. Lack of attachment, disruption or loss can affect a child emotionally and psychologically and impact relationships as it enters adulthood.