A Hierarchical Fuzzy Inference System for Evaluating Cyclist Training Performance

Abstract

This paper proposes a method to obtain the quality of a cyclist’s training session based on training zone, heart rate, and power. Our proposal is called FuCycling (Fuzzy and CYcling). We propose a hierarchical fuzzy inference system that is applied in two phases. The first phase evaluates three input variables: training zone, heart rate, and power; the output variable is performance. In the second phase, the output variable performance will be an input variable, adding a training zone and perceived exertion rating. The output in the second phase is the final output, called session quality. Using this proposed method, a sports coach can review the quality of the cyclist’s session for further feedback on the training plan objectives. We also developed a web application to enable a sports coach to evaluate the dataset and visualize the quality rating of the session in a dashboard, training statistics, the time elapsed in the training zones, and a route map to show the training evaluation.

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