A framework for health behavior change using companionable robots

Abstract

In this paper, we describe a dialogue system framework for a companionable robot, which aims to guide patients towards health behavior changes via natural language analysis and generation. The framework involves three broad stages, rapport building and health topic identification, assess patient's opinion of change, and designing plan and closing session. The framework uses concepts from psychology, computational linguistics, and machine learning and builds on them. One of the goals of the framework is to ensure that the Companionbot builds and maintains rapport with patients.