Personalized Feedback, Guidance, and Motivation for Older Adults Exercising

While exercising, there is no “one size fits all” approach. Each individual reacts differently to various forms of feedback, which highlights the importance of tailoring exercise programs to meet each person’s unique needs and preferences. My research focuses on this personalized approach by utilizing a conversational robot. This robot engages users from the very first interaction, analyzing their attitudes towards exercising, their expressed motivations, and their mental states.

These initial conversations can provide invaluable insights, enabling exercise coaches and physical therapists to accurately gauge a person’s motivation level and tailor the coaching style right from the start. This adaptive interaction helps to develop a personalized feedback style that is not only effective but also enjoyable, fostering a positive and sustainable relationship with physical activity. By integrating user-specific preferences, this project aims to motivate aging adults to engage in exercise with a robotic exercise coach.

This work is being done under the supervision of Dr. Aaron Steinfeld, in collaboration with Roshni Kaushik and Dr. Reid Simmons, at Carnegie Mellon University.

All work is funded through the AI-CARING project.