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Functional Data Analysis of Rowing Technique Using Motion Capture Data

Published: 10 October 2019 Publication History

Abstract

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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Cited By

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  • (2024)Intelligent Pose Recognition and Evaluation System for Rowing Sports2024 5th International Conference on Electronic Communication and Artificial Intelligence (ICECAI)10.1109/ICECAI62591.2024.10674930(620-625)Online publication date: 31-May-2024
  • (2022)A Tensor‐based Regression Approach for Human Motion PredictionQuality and Reliability Engineering International10.1002/qre.315339:2(481-499)Online publication date: 21-Jun-2022
  • (2021)A Systematic Review of the Application of Camera-Based Human Pose Estimation in the Field of Sport and Physical ExerciseSensors10.3390/s2118599621:18(5996)Online publication date: 7-Sep-2021

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cover image ACM Other conferences
MOCO '19: Proceedings of the 6th International Conference on Movement and Computing
October 2019
23 pages
ISBN:9781450376549
DOI:10.1145/3347122
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 October 2019

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Author Tags

  1. Functional Data Analysis
  2. Motion Capture
  3. Movement Visualization
  4. Rowing

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MOCO '19

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Overall Acceptance Rate 85 of 185 submissions, 46%

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Cited By

View all
  • (2024)Intelligent Pose Recognition and Evaluation System for Rowing Sports2024 5th International Conference on Electronic Communication and Artificial Intelligence (ICECAI)10.1109/ICECAI62591.2024.10674930(620-625)Online publication date: 31-May-2024
  • (2022)A Tensor‐based Regression Approach for Human Motion PredictionQuality and Reliability Engineering International10.1002/qre.315339:2(481-499)Online publication date: 21-Jun-2022
  • (2021)A Systematic Review of the Application of Camera-Based Human Pose Estimation in the Field of Sport and Physical ExerciseSensors10.3390/s2118599621:18(5996)Online publication date: 7-Sep-2021

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