Johns Hopkins University

This Johns Hopkins effort advances a digital ecosystem that pairs a socially assistive robot with an interaction app for a Fitbit activity tracker to encourage and monitor physical activity among community-dwelling older adults. The system combines a robotic character for engagement, a touchscreen for exercise demonstrations, and sensing to assess movement quality and repetition counts. Integrated notifications, feedback, and wearable data (e.g., steps and heart rate) enable individualized guidance while generating continuous, objective information on exercise performance and adherence.The team brings complementary expertise in nursing science, human–robot interaction, and behavioral interventions. Principal investigator Junxin Li specializes in personalized physical activity programs to support physical function, sleep, and cognition in older adults and leads related NIH-funded work. Co-investigator Chien-Ming Huang focuses on social robotics and has deployed interactive robots for behavioral and cognitive support in real-world settings. Together, they aim to deliver an accessible, home-based technology that increases motivation, supports tailored coaching, and captures high-resolution data to inform care and optimize outcomes.