An artificial neural network approach for predicting kinematics in handball throws

(Ein künstlicher neuronaler Netzwerkansatz zur Vorhersage der Kinematik von Handballwürfen)

The purpose of this study was to test a new method to predict the kinematics of center of mass (COM) during the take-off phase of the handball shot by mean of multilayer perceptron neural networks (MLPs) based on data from only the force platform. Ten trials` of handball jump shot data from the force platform were obtained. The kinetic data of jump shot trials (force, impulse, and work) were used to feed the net and the data from the force platform kinematics (acceleration, velocity, and displacement) was used to evaluate the production data of the MLP neural network model. A commercial artificial neural network software was used to predict the target kinematic parameters (NeuroDimension, 2014®). The Pearson correlations of all Kinetics parameters between the original and production data was >0.99. The MLPs model successfully predicted the target kinematics depending on kinetics in the handball jump shot under the conditions of this study.
© Copyright 2017 American Journal of Sports Science. Science Publishing Group. Alle Rechte vorbehalten.

Schlagworte: Handball Modellierung Biomechanik Beschleunigung Geschwindigkeit Kraft Neurophysiologie Wurf
Notationen: Biowissenschaften und Sportmedizin Spielsportarten
DOI: 10.11648/j.ajss.20170505.13
Veröffentlicht in: American Journal of Sports Science
Veröffentlicht: 2017
Jahrgang: 5
Heft: 5
Seiten: 35-39
Dokumentenarten: Artikel
Sprache: Englisch
Level: hoch