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A global view on how local muscular fatigue affects human performance

dc.contributor.authorGoethel, Marcio F.
dc.contributor.authorGoncalves, Mauro [UNESP]
dc.contributor.authorBrietzke, Cayque
dc.contributor.authorCardozo, Adalgiso C. [UNESP]
dc.contributor.authorVilas-Boas, Joao P.
dc.contributor.authorErvilha, Ulysses F.
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.contributor.institutionUniv Porto
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2021-06-25T12:18:58Z
dc.date.available2021-06-25T12:18:58Z
dc.date.issued2020-08-18
dc.description.abstractThere is a growing interest in scientific literature on identifying how and to what extent interventions applied to a specific body region influence the responses and functions of other seemingly unrelated body regions. To investigate such a construct, it is necessary to have a global multivariate model that considers the interaction among several variables that are involved in a specific task and how a local and acute impairment affects the behavior of the output of such a model. We developed an artificial neural network (ANN)-based multivariate model by using parameters of motor skills obtained from kinematic, postural control, joint torque, and proprioception variables to assess the local fatigue effects of the abductor hip muscles on the functional profile during a single-leg drop landing and a squatting task. Findings suggest that hip abductor muscles' local fatigue produces a significant effect on a general functional profile, built on different control systems. We propose that expanded and global approaches, such as the one used in this study, have great applicability and have the potential to serve as a tool that guaran-tees ecological validity of future investigations.en
dc.description.affiliationUniv Sao Paulo, Sch Arts Sci & Humanities, Lab Phys Act Sci, BR-03828000 Sao Paulo, Brazil
dc.description.affiliationUniv Porto, Fac Sport, Ctr Res Educ Innovat & Intervent Sport, P-4200450 Porto, Portugal
dc.description.affiliationUniv Porto, Porto Biomech Lab, P-4200450 Porto, Portugal
dc.description.affiliationSao Paulo State Univ, Dept Phys Educ, BR-13506692 Rio Claro, Brazil
dc.description.affiliationUniv Sao Paulo, Sch Arts Sci & Humanities, Exercise Psychophysiol Res Grp, BR-03828000 Sao Paulo, Brazil
dc.description.affiliationUnespSao Paulo State Univ, Dept Phys Educ, BR-13506692 Rio Claro, Brazil
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.description.sponsorshipIdCAPES: 88882.315726/2019-01
dc.format.extent19866-19872
dc.identifierhttp://dx.doi.org/10.1073/pnas.2007579117
dc.identifier.citationProceedings Of The National Academy Of Sciences Of The United States Of America. Washington: Natl Acad Sciences, v. 117, n. 33, p. 19866-19872, 2020.
dc.identifier.doi10.1073/pnas.2007579117
dc.identifier.issn0027-8424
dc.identifier.urihttp://hdl.handle.net/11449/209447
dc.identifier.wosWOS:000567818900015
dc.language.isoeng
dc.publisherNatl Acad Sciences
dc.relation.ispartofProceedings Of The National Academy Of Sciences Of The United States Of America
dc.sourceWeb of Science
dc.subjectartificial neural network
dc.subjectself-organizing feature maps
dc.subjectexercise
dc.subjectfatigue
dc.titleA global view on how local muscular fatigue affects human performanceen
dc.typeArtigo
dcterms.rightsHolderNatl Acad Sciences
dspace.entity.typePublication
unesp.author.orcid0000-0003-4382-0159[1]
unesp.author.orcid0000-0002-7557-3140[3]
unesp.campusUniversidade Estadual Paulista (UNESP), Instituto de Biociências, Rio Claropt
unesp.departmentEducação Física - IBpt

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