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    Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/64339

    Título
    A beta version of an application based on computer vision for the assessment of knee valgus angle: A validity and reliability study
    Autor
    Ceballos Laita, LuisAutoridad UVA
    Marimon, Xavier
    Masip Alvarez, Albert
    Cabanillas Barea, Sara
    Jiménez del Barrio, SandraAutoridad UVA
    Carrasco Uribarren, Andoni
    Año del Documento
    2023
    Editorial
    MDPI
    Descripción
    Producción Científica
    Documento Fuente
    Healthcare, 2023, Vol. 11, Nº. 9, 1258
    Resumen
    Background: In handball, the kinematics of the frontal plane seem to be one of the most important factors for the development of lower limb injuries. The knee valgus angle is a fundamental axis for injury prevention and is usually measured with 2D systems such as Kinovea software (Version 0.9.4.). Technological advances such as computer vision have the potential to revolutionize sports medicine. However, the validity and reliability of computer vision must be evaluated before using it in clinical practice. The aim of this study was to analyze the test-retest and inter-rater reliability and the concurrent validity of a beta version app based on computer vision for the measurement of knee valgus angle in elite handball athletes. Methods: The knee valgus angle of 42 elite handball athletes was measured. A frontal photo during a single-leg squat was taken, and two examiners measured the angle by the beta application based on computer vision at baseline and at one-week follow-up to calculate the test-retest and inter-rater reliability. A third examiner assessed the knee valgus angle using 2D Kinovea software to calculate the concurrent validity. Results: The knee valgus angle in the elite handball athletes was 158.54 ± 5.22°. The test-retest reliability for both examiners was excellent, showing an Intraclass Correlation Coefficient (ICC) of 0.859–0.933. The inter-rater reliability showed a moderate ICC: 0.658 (0.354–0.819). The standard error of the measurement with the app was stated between 1.69° and 3.50°, and the minimum detectable change was stated between 4.68° and 9.70°. The concurrent validity was strong r = 0.931; p < 0.001. Conclusions: The computer-based smartphone app showed an excellent test-retest and inter-rater reliability and a strong concurrent validity compared to Kinovea software for the measurement of the knee valgus angle.
    Materias (normalizadas)
    Athletes
    Atletas
    Kinematics
    Cinemática
    Computer vision
    Visión artificial (Robótica)
    Medicina deportiva
    Knee - Wounds and injuries
    Rodilla - Lesiones y heridas
    Medical care
    Sports medicine
    Materias Unesco
    32 Ciencias Médicas
    2411.06 Fisiología del Ejercicio
    3314 Tecnología Médica
    ISSN
    2227-9032
    Revisión por pares
    SI
    DOI
    10.3390/healthcare11091258
    Version del Editor
    https://www.mdpi.com/2227-9032/11/9/1258
    Propietario de los Derechos
    © 2023 The authors
    Idioma
    eng
    URI
    https://uvadoc.uva.es/handle/10324/64339
    Tipo de versión
    info:eu-repo/semantics/publishedVersion
    Derechos
    openAccess
    Aparece en las colecciones
    • DEP11 - Artículos de revista [241]
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    A-Beta-Version-of-an-Application-Based-on-Computer-Vision.pdf
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