FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3089584610> ?p ?o ?g. }

• W3089584610 abstract "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 and distinguishing their intra-individual changes over time. The objective of this investigation is to analyze biomechanically described movement patterns during the fatigue-related accumulation process within a single training session of a high number of repeated executions of a ballistic sports movement-specifically, the frontal foot kick (mae-geri) in karate-in expert athletes. The two leading research questions presented for consideration are (1) Can characteristics of individual movement patterns be observed throughout the entire training session despite continuous changes, i.e., even as fatigue-related processes increase? and (2) How do intra-individual movement patterns change as fatigue-related processes increase throughout a training session? Sixteen expert karatekas performed 606 frontal foot kicks directed toward an imaginary target. The kicks were performed in nine sets at 80% (K-80) of the self-experienced maximal intensity. In addition, six kicks at maximal intensity (K-100) were performed after each of the nine sets. Between the sets, the participants took a 90-s break. Three-dimensional full-body kinematic data of all kicks were recorded with 10 infrared cameras. The normalized waveforms of nine upper- and lower-body joint angles were classified using a supervised machine learning method (support vector machine). The results of the classification revealed a disjunct distinction between the kinematic movement patterns of individual athletes. The identification of unique movement patterns of individual athletes was independent of the intensity and the degree of fatigue-related processes. In other words, even with the accumulation of fatigue-related processes, the unique movement patterns of an individual athlete can be clearly identified. During the training session, changes in intra-individual movement patterns could also be detected, indicating the occurrence of adaptations in individual movement patterns throughout the fatigue-related accumulation process. The results suggest that these adaptations can be modeled in terms of changes in patterns rather than increasing variance. Practical consequences are critically discussed." @default.
• W3089584610 created "2020-10-08" @default.
• W3089584610 creator A5012647523 @default.
• W3089584610 creator A5043566387 @default.
• W3089584610 creator A5052704769 @default.
• W3089584610 creator A5068204794 @default.
• W3089584610 creator A5081508168 @default.
• W3089584610 date "2020-09-30" @default.
• W3089584610 modified "2023-10-18" @default.
• W3089584610 title "Fatigue-Related and Timescale-Dependent Changes in Individual Movement Patterns Identified Using Support Vector Machine" @default.
• W3089584610 cites W1499230781 @default.
• W3089584610 cites W1902995074 @default.
• W3089584610 cites W1967390580 @default.
• W3089584610 cites W1971419171 @default.
• W3089584610 cites W1971679932 @default.
• W3089584610 cites W1984712386 @default.
• W3089584610 cites W1984861887 @default.
• W3089584610 cites W1987262989 @default.
• W3089584610 cites W1988812042 @default.
• W3089584610 cites W1989166584 @default.
• W3089584610 cites W1990367521 @default.
• W3089584610 cites W1992598308 @default.
• W3089584610 cites W1994518246 @default.
• W3089584610 cites W1996970591 @default.
• W3089584610 cites W2005631973 @default.
• W3089584610 cites W2018773970 @default.
• W3089584610 cites W2020287812 @default.
• W3089584610 cites W2021742495 @default.
• W3089584610 cites W2023722569 @default.
• W3089584610 cites W2025416516 @default.
• W3089584610 cites W2041458101 @default.
• W3089584610 cites W2046329526 @default.
• W3089584610 cites W2047329680 @default.
• W3089584610 cites W2048995539 @default.
• W3089584610 cites W2053082706 @default.
• W3089584610 cites W2069198019 @default.
• W3089584610 cites W2077153934 @default.
• W3089584610 cites W2078672925 @default.
• W3089584610 cites W2079659544 @default.
• W3089584610 cites W2087347434 @default.
• W3089584610 cites W2089465543 @default.
• W3089584610 cites W2089528612 @default.
• W3089584610 cites W2090141326 @default.
• W3089584610 cites W2091026426 @default.
• W3089584610 cites W2091836804 @default.
• W3089584610 cites W2092929114 @default.
• W3089584610 cites W2100522301 @default.
• W3089584610 cites W2103998355 @default.
• W3089584610 cites W2108995755 @default.
• W3089584610 cites W2111148036 @default.
• W3089584610 cites W2112700189 @default.
• W3089584610 cites W2119821739 @default.
• W3089584610 cites W2142565564 @default.
• W3089584610 cites W2149590363 @default.
• W3089584610 cites W2150625542 @default.
• W3089584610 cites W2157227034 @default.
• W3089584610 cites W2165453261 @default.
• W3089584610 cites W2169013317 @default.
• W3089584610 cites W2271146824 @default.
• W3089584610 cites W2276372996 @default.
• W3089584610 cites W2326336506 @default.
• W3089584610 cites W2478245175 @default.
• W3089584610 cites W2484800098 @default.
• W3089584610 cites W2502823620 @default.
• W3089584610 cites W2512532091 @default.
• W3089584610 cites W2539199344 @default.
• W3089584610 cites W2551619218 @default.
• W3089584610 cites W2613867659 @default.
• W3089584610 cites W2615725614 @default.
• W3089584610 cites W2626959333 @default.
• W3089584610 cites W2752497979 @default.
• W3089584610 cites W2754792003 @default.
• W3089584610 cites W2781967300 @default.
• W3089584610 cites W2898474108 @default.
• W3089584610 cites W2902224251 @default.
• W3089584610 cites W2921691056 @default.
• W3089584610 cites W2952505933 @default.
• W3089584610 cites W2962218664 @default.
• W3089584610 cites W2966018667 @default.
• W3089584610 cites W2971108714 @default.
• W3089584610 cites W2980820319 @default.
• W3089584610 cites W2998466307 @default.
• W3089584610 cites W30160013 @default.
• W3089584610 cites W3037979604 @default.
• W3089584610 cites W4211003818 @default.
• W3089584610 cites W4235419611 @default.
• W3089584610 cites W4248918020 @default.
• W3089584610 cites W4299869464 @default.
• W3089584610 doi "https://doi.org/10.3389/fpsyg.2020.551548" @default.
• W3089584610 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7554555" @default.
• W3089584610 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33101124" @default.
• W3089584610 hasPublicationYear "2020" @default.
• W3089584610 type Work @default.
• W3089584610 sameAs 3089584610 @default.
• W3089584610 citedByCount "13" @default.
• W3089584610 countsByYear W30895846102020 @default.
• W3089584610 countsByYear W30895846102021 @default.
• W3089584610 countsByYear W30895846102022 @default.
• W3089584610 countsByYear W30895846102023 @default.
• W3089584610 crossrefType "journal-article" @default.

• next