Combining Inertial Sensors and Machine Learning to Predict vGRF and Knee Biomechanics during a Double Limb Jump Landing Task.

Chaaban, Courtney R; Berry, Nathaniel T; Armitano-Lago, Cortney; Kiefer, Adam W; Mazzoleni, Michael J; Padua, Darin A

Chaaban, Courtney R; Berry, Nathaniel T; Armitano-Lago, Cortney; Kiefer, Adam W; Mazzoleni, Michael J; Padua, Darin A.

Afiliación

Chaaban CR; Department of Exercise and Sport Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Berry NT; Department of Kinesiology, University of North Carolina at Greensboro, Greensboro, NC 27402, USA.
Armitano-Lago C; Under Armour, Inc., Baltimore, MD 21230, USA.
Kiefer AW; Department of Exercise and Sport Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Mazzoleni MJ; Department of Exercise and Sport Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Padua DA; Department of Exercise and Sport Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.

Sensors (Basel) ; 21(13)2021 Jun 26.

Article en En | MEDLINE | ID: mdl-34206782

Asunto(s)

Lesiones del Ligamento Cruzado Anterior; Articulación de la Rodilla; Fenómenos Biomecánicos; Humanos; Rodilla; Aprendizaje Automático; Adulto Joven

Palabras clave

biomechanics; inertial sensors; jump landing; machine learning; return to sport testing

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Lesiones del Ligamento Cruzado Anterior / Articulación de la Rodilla Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Adult / Humans Idioma: En Revista: Sensors (Basel) Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos

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