Examinando por Autor "Silvestre Aguirre, Rony"

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    Ítem
    Efectos de la manipulación vertebral de alta velocidad en las propiedades biomécanicas del recto anterior del admomen en sujetos sanos
    (Universidad Andrés Bello, 2019) Maray M., Aníbal; Zamorano S., Benjamin; Silvestre Aguirre, Rony; Facultad de Ciencias de la Rehabilitación; Escuela de Kinesiología
    La manipulación de alta velocidad es utilizada de manera frecuente dentro de la terapia manual y numerosos estudios avalan sus beneficios, sin embargo, sus efectos sobre propiedades mecánicas del músculo aún es poco comprendido, encontrándose aún gran parte de la literatura con resultados poco concluyentes. Objetivo: Determinar los efectos de la manipulación vertebral torácica de altavelocidad, sobre las propiedades mecánicas del músculo recto anterior del abdomen en sujetos sanos. Diseño: Estudio de intervención cuasi experimental. Materiales y métodos: La intervención se realizará a nivel del segmento T7- T8, por un Quiropráctico certificado y con experiencia en la manipulación vertebral de alta velocidad. Los cambios en las propiedades mecánicas del músculo serán evaluados antes y después de la intervención, mediante el uso del MyotonPRO. Resultados: Los resultados son estadísticamente significativos y no demuestran una diferencia en los parámetros de Stiffness (n/m) ni de frecuencia oscilatoria (Hz). Conclusiones: La manipulación vertebral de alta velocidad no genera cambios en el control neural del tono muscular del sistema gamma por medio de la estimulación de fibras tipo II articulares.
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    Ítem
    Explainable Machine Learning Techniques to Predict Muscle Injuries in Professional Soccer Players through Biomechanical Analysis
    (MDPI, 2024-01) Calderón-Díaz, Mailyn; Silvestre Aguirre, Rony; Vásconez, Juan P.; Yáñez, Roberto; Roby, Matías; Querales, Marvin; Salas, Rodrigo
    There is a significant risk of injury in sports and intense competition due to the demanding physical and psychological requirements. Hamstring strain injuries (HSIs) are the most prevalent type of injury among professional soccer players and are the leading cause of missed days in the sport. These injuries stem from a combination of factors, making it challenging to pinpoint the most crucial risk factors and their interactions, let alone find effective prevention strategies. Recently, there has been growing recognition of the potential of tools provided by artificial intelligence (AI). However, current studies primarily concentrate on enhancing the performance of complex machine learning models, often overlooking their explanatory capabilities. Consequently, medical teams have difficulty interpreting these models and are hesitant to trust them fully. In light of this, there is an increasing need for advanced injury detection and prediction models that can aid doctors in diagnosing or detecting injuries earlier and with greater accuracy. Accordingly, this study aims to identify the biomarkers of muscle injuries in professional soccer players through biomechanical analysis, employing several ML algorithms such as decision tree (DT) methods, discriminant methods, logistic regression, naive Bayes, support vector machine (SVM), K-nearest neighbor (KNN), ensemble methods, boosted and bagged trees, artificial neural networks (ANNs), and XGBoost. In particular, XGBoost is also used to obtain the most important features. The findings highlight that the variables that most effectively differentiate the groups and could serve as reliable predictors for injury prevention are the maximum muscle strength of the hamstrings and the stiffness of the same muscle. With regard to the 35 techniques employed, a precision of up to 78% was achieved with XGBoost, indicating that by considering scientific evidence, suggestions based on various data sources, and expert opinions, it is possible to attain good precision, thus enhancing the reliability of the results for doctors and trainers. Furthermore, the obtained results strongly align with the existing literature, although further specific studies about this sport are necessary to draw a definitive conclusion.