A proposal for an AI-based toy to encourage and assess symbolic play in autistic children

In this paper, we provide an in-depth description of Echo, an interactive, smart toy, designed to encourage the symbolic play in autistic children. Symbolic play is a key competence in the cognitive development, and it is observed for instance when a child uses an object to represent other objects. The toy, characterised by an abstract shape, can autonomously recognise how the user handles it during play (e.g. mimicking the movements of a car, an aeroplane, a frog in this study) and produce, as rewarding feedback, distinctive sensory outputs such as colours and sounds, according to the detected imaginary toy. The categorisation, achieved with an average accuracy of 90.1%, is carried out in real-time by a Machine Learning (ML) model, which runs in the device's embedded electronics; the ML model was trained using the data by an onboard IMU sensor, which provides information about the toy movements (i.e. tilt, angular velocity, acceleration). The paper provides an overview of the toy design and functionalities, and presents the results of a feasibility test with neurotypical adult participants. Finally, it proposes Echo as a potential tool to encourage, through the AI-mediated sensory feedback, this pivotal competence; symbolic play is in fact often impaired or atypical in autistic children, and new technologies – such as Echo – can provide interesting novel opportunities for neurodevelopmental therapists and researchers.