Personalizing User Engagement Dynamics in a Non-Verbal Communication Game for Cerebral Palsy

TL;DR

This paper presents a personalized engagement model for a socially assistive robot helping individuals with cerebral palsy practice non-verbal communication, demonstrating improved user engagement through tailored robot actions.

Contribution

It introduces personalized models of engagement dynamics for a robot assisting people with cerebral palsy, based on data collected from a user study, enhancing interaction effectiveness.

Findings

Participants preferred embodied robots over screen-based agents.

Personalized models improved engagement in users with CP.

The approach offers design insights for future assistive robot systems.

Abstract

Children and adults with cerebral palsy (CP) can have involuntary upper limb movements as a consequence of the symptoms that characterize their motor disability, leading to difficulties in communicating with caretakers and peers. We describe how a socially assistive robot may help individuals with CP to practice non-verbal communicative gestures using an active orthosis in a one-on-one number-guessing game. We performed a user study and data collection with participants with CP; we found that participants preferred an embodied robot over a screen-based agent, and we used the participant data to train personalized models of participant engagement dynamics that can be used to select personalized robot actions. Our work highlights the benefit of personalized models in the engagement of users with CP with a socially assistive robot and offers design insights for future work in this area.