The success of an athlete depends in all sports not only on the physical conditioning (strength, fitness) but also on the specific manner how the movements are executed. The purpose of this project is to develop data analysis methods that can identify features in the movement patterns of athletes that correlate with specific performance variables. This information will help athletes and technical coaches to improve their training programs and performance in competitions.
The data analysis methods developed in this project are derived from pattern recognition approaches. Therefore several measurement methods are combined to acquire as much information about the execution (kinematics, kinetics) and control (electromyography) of specific, performance-related movements as possible. Using Matlab we will then develop algorithms to identify, extract, and visualize movement features correlating with performance. This technique will be applied in alpine skiing, soccer and javelin throwing.