The purpose of the study was to develop an evidence-based method for identification and classification of wheelchair sports (rugby) activities and performance during a match using fractal dimensions. The approach involves five wheelchair rugby athletes of different classifications who were monitored during six different matches using mobile devices with in-built accelerometers. The linear acceleration signals were processed using two different approaches based on calculating fractal dimensions. One was based on Rényi`s entropy, which produced the probability dimension (S0), and the other was based on Hausdorff`s definition, resulting in the Hausdorff dimension (DH). When both dimensions were individually plotted as cumulative distribution plots, they offered two approaches to analyze the performance of a wheelchair rugby athlete. Combining the two dimensions produced a two-dimensional (2D) mapping that identified five different activities of each athlete during a wheelchair rugby match—(1) no activities, (2) low activities, (3) high-speed coasting, (4) high-speed pushing, and (5) extreme collisions. In the 2D mapping, four boundary lines separate the five different activities, which produced a template for each athlete. It was found in this research that the classification and skill level of the athlete had an effect on the boundary line values that form the template. The outcome of the activity identification was also verified by comparing with video footage of the athletes. The method developed in this research has possible applications for coaching, match analysis, and talent identification.
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