Functional data analysis of rowing technique using motion capture data

We present an approach to analyzing the motion capture data of rowers using bivariate functional principal component analysis (bfPCA). The method has been applied on data from six elite rowers rowing on an ergometer. The analyses of the upper and lower body coordination during the rowing cycle revealed significant differences between the rowers, even though the data was normalized to account for differences in body dimensions. We make an argument for the use of bfPCA and other functional data analysis methods for the quantitative evaluation and description of technique in sports.
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Bibliographic Details
Subjects:
Notations:technical and natural sciences endurance sports
Tagging:data mining Datenanalyse
Published in:Proceedings of the 6th International Conference on Movement and Computing
Language:English
Published: New York ACM 2019
Series:MOCO '19
Online Access:https://doi.org/10.1145/3347122.3347135
Pages:Article 12
Document types:article
Level:advanced