Personalized Feedback, Guidance, and Motivation for Older Adults Exercising

When it comes to exercise, there is no one-size-fits-all approach. Each individual responds differently to various forms of feedback, highlighting the need for personalized exercise programs tailored to individual needs and preferences. My research explores this personalized approach through the use of a conversational robot that engages users from their very first interaction.

By delivering adaptive feedback, the robot creates a customized exercise experience that is both effective and enjoyable, fostering a sustainable and positive relationship with physical activity. This project aims to encourage aging adults to maintain regular exercise habits with the support of a robotic exercise coach that adapts to their unique preferences.

Additionally, we investigate how different robot personalities influence users’ perceptions and motivation toward exercise. While some individuals may prefer a structured coaching approach, others might respond better to a social workout companion. By understanding these preferences, we aim to develop robotic exercise assistants that enhance engagement and promote long-term adherence to physical activity.

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.