The elements of modelling leg and monofin movements using a neural network

The aim of the study was to verify the diagnostic value of modelling the monofin swimming technique by means of artificial neural networks in order to optimize the technique of legs and monofin movements. The practical aspect of the modelling of the monofin swimming technique is apparent, since the interpretation of the propulsion as such is much less complicated than it is in the case of traditional swimming. Assuming that the technical level of the swimmers participating in the study is high (elimination of the redundant degree of freedom in the chain of swimmer’s body–monofin) the analysis was limited to the calf, foot and monofin movements. The model of the neural network allowed identifying the differences in the structure of the movements phases, pointing to extra margin that can be used to generate propulsion while making an upward movement and, simultaneously, paving the way to optimize the monofin swimming technique.