The aim of the study was analysis of leg segments displacement and monofin strain in terms of propulsion efficiency. It was assumed that application of Artificial Neural Network enables precise determination of brackets within which the leg segments displacement and monofin strain will achieve optimal scope to gain maximal swimming speed. The response of network pointed 10 parameters. Those chosen to analysis are: foot flexion angle towards shin, proximal fin part flexion angle towards foot, attack angle of the distal fin part, attack angle of fin surface. Comparing network response graph with the results of the real movement analysis validates the results in the modelling sense. Vast network capabilities in developing the analysis with new cases allow for applying the model in monofin swimming technique assessment.
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