Can Individual Movement Characteristics Across Different Throwing Disciplines Be Identified in High-Performance Decathletes?

Although the individuality of whole-body movements has been suspected for years, the scientific proof and systematic investigation that individuals possess unique movement patterns did not manifest until the introduction of the criteria of uniqueness and persistence from the field of forensic scienc...

Full description

Bibliographic Details
Main Authors: Fabian Horst, Daniel Janssen, Hendrik Beckmann, Wolfgang I. Schöllhorn
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-09-01
Series:Frontiers in Psychology
Subjects:
Online Access:https://www.frontiersin.org/article/10.3389/fpsyg.2020.02262/full
id doaj-d41577da290c4c0db2ab14bd3d53ccf6
record_format Article
spelling doaj-d41577da290c4c0db2ab14bd3d53ccf62020-11-25T03:34:25ZengFrontiers Media S.A.Frontiers in Psychology1664-10782020-09-011110.3389/fpsyg.2020.02262561870Can Individual Movement Characteristics Across Different Throwing Disciplines Be Identified in High-Performance Decathletes?Fabian Horst0Daniel Janssen1Hendrik Beckmann2Wolfgang I. Schöllhorn3Department of Training and Movement Science, Institute of Sport Science, Johannes Gutenberg-University Mainz, Mainz, GermanyGymnasium Dionysianum, Rheine, GermanyDepartment of Training and Movement Science, Institute of Sport Science, Johannes Gutenberg-University Mainz, Mainz, GermanyDepartment of Training and Movement Science, Institute of Sport Science, Johannes Gutenberg-University Mainz, Mainz, GermanyAlthough the individuality of whole-body movements has been suspected for years, the scientific proof and systematic investigation that individuals possess unique movement patterns did not manifest until the introduction of the criteria of uniqueness and persistence from the field of forensic science. Applying the criteria of uniqueness and persistence to the individuality of motor learning processes requires complex strategies due to the problem of persistence in the learning processes. One approach is to examine the learning process of different movements. For this purpose, it is necessary to differentiate between two components of movement patterns: the individual-specific component and the discipline-specific component. To this end, a kinematic analysis of the shot put, discus, and javelin throwing movements of seven high-performance decathletes during a qualification competition was conducted. In total, joint angle waveforms of 57 throws formed the basis for the recognition task of individual- and discipline-specific throwing patterns using a support vector machine. The results reveal that the kinematic throwing patterns of the three disciplines could be distinguished across athletes with a prediction accuracy of up to 100% (57 of 57 throws). In addition, athlete-specific throwing characteristics could also be identified across the three disciplines. Prediction accuracies of up to 52.6% indicated that up to 10 out of 19 throws of a discipline could be assigned to the correct athletes, based on only knowing these athletes from the kinematic throwing patterns in the other two disciplines. The results further suggest that individual throwing characteristics across disciplines are more pronounced in shot put and discus throwing than in javelin throwing. Applications for training and learning practice in sports and therapy are discussed. In summary, the chosen approach offers a broad field of application related to the search of individualized optimal movement solutions in sports.https://www.frontiersin.org/article/10.3389/fpsyg.2020.02262/fullmotor learningpattern recognitionhigh-performance sportsmachine learningsupport vector machineindividuality
collection DOAJ
language English
format Article
sources DOAJ
author Fabian Horst
Daniel Janssen
Hendrik Beckmann
Wolfgang I. Schöllhorn
spellingShingle Fabian Horst
Daniel Janssen
Hendrik Beckmann
Wolfgang I. Schöllhorn
Can Individual Movement Characteristics Across Different Throwing Disciplines Be Identified in High-Performance Decathletes?
Frontiers in Psychology
motor learning
pattern recognition
high-performance sports
machine learning
support vector machine
individuality
author_facet Fabian Horst
Daniel Janssen
Hendrik Beckmann
Wolfgang I. Schöllhorn
author_sort Fabian Horst
title Can Individual Movement Characteristics Across Different Throwing Disciplines Be Identified in High-Performance Decathletes?
title_short Can Individual Movement Characteristics Across Different Throwing Disciplines Be Identified in High-Performance Decathletes?
title_full Can Individual Movement Characteristics Across Different Throwing Disciplines Be Identified in High-Performance Decathletes?
title_fullStr Can Individual Movement Characteristics Across Different Throwing Disciplines Be Identified in High-Performance Decathletes?
title_full_unstemmed Can Individual Movement Characteristics Across Different Throwing Disciplines Be Identified in High-Performance Decathletes?
title_sort can individual movement characteristics across different throwing disciplines be identified in high-performance decathletes?
publisher Frontiers Media S.A.
series Frontiers in Psychology
issn 1664-1078
publishDate 2020-09-01
description Although the individuality of whole-body movements has been suspected for years, the scientific proof and systematic investigation that individuals possess unique movement patterns did not manifest until the introduction of the criteria of uniqueness and persistence from the field of forensic science. Applying the criteria of uniqueness and persistence to the individuality of motor learning processes requires complex strategies due to the problem of persistence in the learning processes. One approach is to examine the learning process of different movements. For this purpose, it is necessary to differentiate between two components of movement patterns: the individual-specific component and the discipline-specific component. To this end, a kinematic analysis of the shot put, discus, and javelin throwing movements of seven high-performance decathletes during a qualification competition was conducted. In total, joint angle waveforms of 57 throws formed the basis for the recognition task of individual- and discipline-specific throwing patterns using a support vector machine. The results reveal that the kinematic throwing patterns of the three disciplines could be distinguished across athletes with a prediction accuracy of up to 100% (57 of 57 throws). In addition, athlete-specific throwing characteristics could also be identified across the three disciplines. Prediction accuracies of up to 52.6% indicated that up to 10 out of 19 throws of a discipline could be assigned to the correct athletes, based on only knowing these athletes from the kinematic throwing patterns in the other two disciplines. The results further suggest that individual throwing characteristics across disciplines are more pronounced in shot put and discus throwing than in javelin throwing. Applications for training and learning practice in sports and therapy are discussed. In summary, the chosen approach offers a broad field of application related to the search of individualized optimal movement solutions in sports.
topic motor learning
pattern recognition
high-performance sports
machine learning
support vector machine
individuality
url https://www.frontiersin.org/article/10.3389/fpsyg.2020.02262/full
work_keys_str_mv AT fabianhorst canindividualmovementcharacteristicsacrossdifferentthrowingdisciplinesbeidentifiedinhighperformancedecathletes
AT danieljanssen canindividualmovementcharacteristicsacrossdifferentthrowingdisciplinesbeidentifiedinhighperformancedecathletes
AT hendrikbeckmann canindividualmovementcharacteristicsacrossdifferentthrowingdisciplinesbeidentifiedinhighperformancedecathletes
AT wolfgangischollhorn canindividualmovementcharacteristicsacrossdifferentthrowingdisciplinesbeidentifiedinhighperformancedecathletes
_version_ 1724558923120246784