You Are Doing Great! Only One Rep Left: An Affect-Aware Social Robot for Exercising

Abstract

Regular exercise has immediate and long-term benefits for people of all ages. Maintaining an adequate amount of daily exercise is important to overall health and wellbeing. Our research focuses on the development of a socially assistive robot, Salt, to facilitate different upper body exercises. During the exercises, the robot is uniquely able to autonomously detect a user's affect and engagement as well as measure their heart rate to prevent overexertion. A robot emotion model using an n th order Markov Chain is used to determine the robot's appropriate emotions during interactions based on user affect and engagement, and its own emotion history. Human-robot interaction experiments were conducted to investigate perceived usefulness and acceptance. The results showed that most users were engaged and had positive valence towards the robot during the interactions. Post-experiment questionnaire results also showed they were able to detect the robot's emotions and enjoyed interacting with it.