Human modeling for biomechanical analysis of closed kinetic chain exercises of the leg

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This paper presents the development and validation of a tridimensional 7-DOF human body model for the representation and study of closed kinetic chain exercises (CKCE) performed with the feet fixed in space, i.e. low posture exercises. The biomechanical model, a link-segment model, is based on an Eu...

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Detalles Bibliográficos
Autores: Chicoma C.G., Canales F.G., Garcia J.G., Morales M., Elias D.A., Villota E.R.
Formato: artículo
Fecha de Publicación:2019
Institución:Consejo Nacional de Ciencia Tecnología e Innovación
Repositorio:CONCYTEC-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.concytec.gob.pe:20.500.12390/2732
Enlace del recurso:https://hdl.handle.net/20.500.12390/2732
https://doi.org/10.1007/978-3-030-16423-2_13
Nivel de acceso:acceso abierto
Materia:Experimental validation
Biomechanical analysis
Body model
CKCE
http://purl.org/pe-repo/ocde/ford#3.04.01
Descripción
Sumario:This paper presents the development and validation of a tridimensional 7-DOF human body model for the representation and study of closed kinetic chain exercises (CKCE) performed with the feet fixed in space, i.e. low posture exercises. The biomechanical model, a link-segment model, is based on an Euler-Lagrange formulation and employs a generalized joint coordinate system. A top-down mechanical analysis provides an estimation of the internal joint moments, along with the vertical ground reaction forces, using kinematical data collected by inertial sensors. The model is validated by correlating estimated ground reaction forces to kinetic experimental data from force plates. Pearson correlation coefficients were calculated for four CKCE types (150 trials in total). In all cases, a median correlation r > 0.90 was found, hence proving that the proposed model is quite satisfactory for CKCE movement representation and analysis. Volleyball serve reception in low posture, a type of CKCE, is also analyzed using the results of the model. © Springer Nature Switzerland AG 2019.
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La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).