Interval training guidance system with music and wireless group exercise motivations

Abstract

Interval training is a well known exercise protocol which helps strengthen and improve one's cardiovascular fitness. It interleaves high intensity exercises with rest periods. Despite the known benefits, proper scheduling and completion of interval training routines are not easy to perform. For example, without expensive equipment such as a treadmill, there is almost no way to figure out one's speed for proper imitation of a given exercise protocol, and thus interval training is heavily dependent on individual motivation levels. In this work, we use behavioral cueing using music and performance feedback to provide motivation during interval training exercise sessions. We have developed an application program on the popular iPhone platform. Our game-like and social networking application guides the user using exercise music. By measuring performance of the user through sensor readings, specifically accelerometers embedded in the iPhone, we are able to play the right song to match the user's workout plan. A hybrid of a collaborative, content, and context-aware filtering algorithm incorporates the user's music preferences and the exercise speed that will enhance performance. Additionally, adherence to an exercise protocol and the amount of calories burned is translated into a score that is sent to the user's social network group.