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2024-09-01
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info:eu-repo/semantics/openAccess
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Resumen
This paper explores the application of intelligent psychomotor systems to enhance basketball free-throw performance through the Sensing, Modeling, Design and Delivery (SMDD) framework. The focus of this paper is on helping players improve basketball free-throw mechanics using data gathered from video and accelerometers, identifying key factors influencing shot success, with the ultimate goal of actionable feedback (meaning that the suggested adjustments need to be practical for the learner to implement). This includes data cleaning, signal synchronization, segmentation of time series, labeling, and modeling among others. However, the analysis revealed limitations in the models developed, due to the small-sized dataset, which hindered the identification of key factors and the feedback design. However, although the results were constrained to a limited dataset, the methodology developed shows the potential of psychomotor movement modeling and targeted feedback to significantly improve shooting accuracy. The need for a more extensive data collection is thus highlighted, with a methodological contribution in the form of a checklist for useful data collection in this context.
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Categorías UNESCO
Palabras clave
hardware, digital signal processing, communication hardware, interfaces and storage, general and reference, design, human-centered computing, human computer interaction (HCI), applied computing, education
Citación
García Arce, Pablo. Trabajo Fin de Máster: Some methodological insights to build intelligent psychomotor systems for enhancing skill acquisition in free-throw shooting through personalized feedback in basketball. Universidad Nacional de Educación a Distancia (UNED), 2024
Centro
E.T.S. de Ingeniería Informática
Departamento
Inteligencia Artificial