An effort control system for training elite team-sport athletes

This paper presents a novel system for effort control in team-sport training, where each component is associated with a particularized program. The system relies on a decision engine that analyzes training data and provides instructions to athletes, and on a sensing infrastructure which monitors athletes´ biometrics and movements and gathers environmental data such as humidity or temperature. The prototype has been developed using IMOTE2 and MicaZ sensors under TinyOS and BioHarness biometric belts. The decision technique estimates the ratios of each effort regime, based on best-fit polynomial approximations using historical data from previous training sessions. The complete system results in a virtual coach, operating in real time and automatically. This methodology has been piloted in an experiment with the UCAM Volleyball Murcia team, top of the Spanish national women´s volleyball league. Data obtained during training sessions have provided a knowledge base for the algorithms developed and allowed for validation of the results.