Fatigue-Related and Timescale-Dependent Changes in Individual Movement Patterns Identified Using Support Vector Machine

Fatigue-Related and Timescale-Dependent Changes in Individual Movement Patterns Identified Using Support Vector Machine

The scientific and practical fields—especially high-performance sports—increasingly request a stronger focus be placed on individual athletes in human movement science research. Machine learning methods have shown efficacy in this context by identifying the unique movement patterns of individuals an...

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Bibliographic Details
Main Authors: Johannes Burdack, Fabian Horst, Daniel Aragonés, Alexander Eekhoff, Wolfgang Immanuel Schöllhorn
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-09-01
Series:Frontiers in Psychology
Subjects:
situatedness
individuality
kinematic data
optimal movement
fatigue
support vector machine
Online Access:https://www.frontiersin.org/article/10.3389/fpsyg.2020.551548/full

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