Classification methods can identify external constrains in swimming
Auteur(s): Rafaila Grigoriou, Thomas Nikodelis, Dimitris Kugiumtzis, Irkalis A.Kollias
Année de publication: 2018
Journal: Journal of Biomechanics
Outil de mesure utilisé: KFORCE Plates
Accéder à la publication: https://www.researchgate.net/publication/328727272_Classification_methods_can_identify_external_constrains_in_swimming
Résumé: The purpose of the present study is to examine whether the use of fins is identifiable based on swimmers’ technique and to find out technique-related features that depict fins’ influence. First, a number of features were extracted from kinematic data given by movement sensors attached to swimmers’ bodies during butterfly swimming technique. Then, dimensionality reduction, feature selection and classification methods were applied to the extracted features. Two classification tasks were defined, one for the three classes of long, short and no fins, attaining accuracy up to 70, 62 and 70%, respectively, and the two-class simplified version (long fins, no fins) with accuracy up to 78%. These high accuracy levels were also found statistically significant and suggest that the use of fins influences swimming technique in a recognizable way and that the selected features that depict those differences are swimming type depended.
