Modeling Motivational States Through Interpreting Physical Activity Data for Adaptive Robot Companions

This research aims to develop an adaptive human-robot interaction system that works with users over long periods of time to achieve a common goal that is beneficial to the user. The particular scenario I focus on is that of a robot companion interacting with adolescents, helping them succeed at achieving daily physical activity goals. To develop such a system, I propose a method of modeling the user’s motivational state and employing this model in order to adapt motivational strategies best suited for each user. The proposed system uses both physical activity data obtained from wearable sensors (such as wristband devices) and information acquired by the robot from its interaction partners. 1 Problem and Motivation The benefits of physical activity are well known, as research shows that daily physical activity has wide-ranging benefits, from improving cognitive and academic performance to helping with bone development and health [17]. My work seeks to sustain these benefits with robot home companions through personalized, data-driven coaching. The U. S. Department of Health and Human Services comprehensive guidelines on physical activity for individuals ages 6 and older state that children and adolescents should aim to accumulate at least 60 minutes of moderateor vigorous-intensity aerobic physical activity on most days of the week, preferably daily [1]. Current evidence shows that levels of physical activity among youth remain low, and that levels of physical activity decline dramatically during adolescence [2]. These data show the importance of developing methods to keep adolescents on track to achieving daily-recommended levels of physical activity. With this in mind, I seek to develop a human-robot interaction system that motivates adolescents to engage in physical activity on a daily basis. 2 Background and Related Work There exists a great deal of work concerning health and well-being applications, such as commercial systems that use motivational strategies to help users stay