A Personalized Pacing System for Real-Time Physical Activity Advising

Abstract

We design and implement an intelligent advisor system for assisting individuals in changing their physical activity behavior. This system monitors an individual's physical activity and provides personalized, dynamic, pace-based recommendations to help an individual attain his/her activity goal. It adapts to a person's real-life constraints and generates recommendations using data from the individual's own activity history as well as data from a cohort of people similar to the individual. Our system relies on frequent predictions of the likelihood of goal attainment throughout the day, so that the current conditions and context are accounted for.