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  Recurrence analysis discriminates martial art movement patterns

Straiotto, B. G., Marwan, N., James, D. C., Seeley, P. J. (2023): Recurrence analysis discriminates martial art movement patterns. - European Physical Journal - Special Topics, 232, 1, 151-159.
https://doi.org/10.1140/epjs/s11734-022-00684-6

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 Creators:
Straiotto, B. G.1, Author
Marwan, Norbert2, Author              
James, D. C.1, Author
Seeley, P. J.1, Author
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Abstract: We aimed to determine whether the combined application of principal components and recurrence quantification analyses might serve to discriminate both spatial and temporal differences between backwards-forwards movement patterns. Elite (n = 9) and nonelite (n = 9) martial artists were recorded using motion capture techniques and features of whole-body movement defined at the segment level were investigated by principal components analysis. For both groups of subjects, four movement components explained > 90% of the variability in the data. Given our interest in temporal patterning, the time series derived from scores for each of the principal components were subsequently subjected to recurrence quantification analysis, participant by participant. For the first movement component, statistically significant differences between groups were detected for the recurrence measure determinism (p < 0.05). For the third movement component, statistically significant differences were detected for the recurrence measures laminarity and maxline (p < 0.01). Hence use of a combination of principal components and recurrence techniques revealed quantitative differences between movements of the two subject groups, differences that may represent more skilled motor control in the elite group related to the functional importance of these apparently simple movement patterns.

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Language(s): eng - English
 Dates: 2022-10-102023-02
 Publication Status: Finally published
 Pages: 9
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1140/epjs/s11734-022-00684-6
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Nonlinear Dynamics
Model / method: Nonlinear Data Analysis
Model / method: Quantitative Methods
Working Group: Development of advanced time series analysis techniques
OATYPE: Green Open Access
 Degree: -

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Title: European Physical Journal - Special Topics
Source Genre: Journal, SCI, Scopus, p3
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Pages: - Volume / Issue: 232 (1) Sequence Number: - Start / End Page: 151 - 159 Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/150617
Publisher: Springer