Sensor and computing technologies provide people with information on their performance and load when doing sports. In order to automatically give advices on how to continue exercising and/or to adjust the sports equipment during the physical activity, intelligent devices are required. These devices rely on models for recognition and classification of patterns in the motion currently performed. Different methods and models, such as Neural Networks, Hidden Markov models or Support Vector Machines have proven to be applicable for this purpose. Pros and cons of the different approaches are discussed. Practical applications are presented and experiences reported.
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