AI Article Synopsis

  • The take-off phase in platform diving is crucial for achieving high performance quality and difficulty.
  • A dryland measuring and feedback system was developed to optimize take-off technique, specifically for the dive back 1¼ somersault tucked leading to the dive back 3½ somersault tucked (207 C) from a 10-meter platform.
  • A mathematical model was created through a multi-step examination process analyzing motion parameters from 18 dives performed by elite German divers, which aids in understanding optimal take-off mechanics and allows for personalized training feedback.

Article Abstract

In platform diving the take-off phase is of outstanding importance in order to achieve both a high level of performing quality and a high degree of difficulty. The diver has to produce the right forces and direction of the center of mass (COM) in order to attain the required angular momentum and dive height. To support the development of an optimum take-off technique, the Institute for Applied Training Science designed a dryland measuring and feedback system. Using the example of the dive back 1¼ somersault tucked in preparation for the dive back 3½ somersault tucked (207 C) from the 10-m-platform, kinematic and kinetic reference values for key positions were determined. Therefore, we developed a mathematical model using a multi-step examination plan with the following parts: (1) variables defined using nonparametric correlation analyses r of the motion parameters, (2) statistical modelling to predict values of the parameters, (3) stochastic modelling. The model is based on a selection of 18 dives from 10 different elite divers of the German Swimming Federation (DSV). The approach presented provides helpful insights into the mechanisms of an optimal take-off, enables a target-performance comparison with objective motion parameters and therefore, enables individualized feedback to guide the training process more efficiently.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8607775PMC
http://dx.doi.org/10.2478/hukin-2021-0097DOI Listing

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