The use of socially assistive robots in the design of intelligent cognitive therapies for people with dementia

October 27, 2019

 

Overview

Parents, teachers, and clinicians are struggling today to provide children with enough one-on-one, personalized support. In many schools, teachers don’t have enough time to provide individualized language instruction to the 1 in 5 children who speak a language other than English at home. Clinicians and families struggle to provide individualized educational services to children with social and cognitive deficits, whose numbers have quadrupled in the US in the last decade alone. With more than one third of children and adolescents overweight or obese, parents are struggling to provide the coaching and support needed to help children maintain healthy habits around nutrition and exercise.
We believe that robotics technology can help. Socially assistive robotics (SAR) is a new field of robotics that focuses on assisting users through social rather than physical interaction. Just as a good coach or teacher can provide motivation, guidance, and support, socially assistive robots attempt to provide the appropriate emotional, cognitive, and social cues to encourage development, learning, or therapy for an individual. Our mission is to develop the technology that can make this possible.

Imagine a robot that can …

… guide a child toward long-term behavioral goals;

… be customized to the particular needs of the child;

… develop and change as the child does;

… engage the child as a peer, not as a parent, teacher, toy, or pet.

To achieve this vision, this Expedition will advance the state-of-the-art in socially assistive human-robot interaction from short-term interactions in structured environments to long-term interactions that are adaptive, engaging, and effective. This progress will require transformative computing research in three broad and naturally interrelated research areas:

1) The Expedition will develop computational models of the dynamics of social interaction, so that robots can automatically detect, analyze, and influence agency, intention, and other social interaction primitives in dynamic environments.

2) The Expedition will develop machine learning algorithms that adapt and personalize interactions to individual physical, social, and cognitive differences, enabling robots to teach and shape behavior in ways that are tailored to the needs, preferences, and capabilities of each individual.

3) The Expedition will develop systems that guide children toward specific learning goals over periods of weeks and months, allowing for truly long-term guidance and support.

This Expedition has the potential to substantially impact the effectiveness of education and healthcare for children, and the technological tools developed will serve as the basis for enhancing the lives of children and other groups that require specialized support and intervention. The proposed computing research is tied to a comprehensive student training program, bringing a compelling, engaging, and grounded STEM experience to K-12 students through in-school and after-school activities. It also establishes an annual training summit to provide undergraduates with the multi-disciplinary background to engage in this promising research area in graduate school. Finally, by establishing a brand name for socially assistive robotics, this effort will create a central authority for the distribution of high-quality, peer-reviewed information, providing a coherent focal point for enhancing outreach and education.

Yale University Publication, 2019 - NSF Grant