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https://hdl.handle.net/2183/45880 Monitorización e clasificación de golpes de tenis con sensores inerciais e aprendizaxe máquina
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Barcia Facal, Julián
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Universidade da Coruña. Facultade de Informática
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Abstract
[Resumo]: Este proxecto céntrase no desenvolvemento dun sistema innovador para a monitorización e clasificación dos golpes de tenis utilizando sensores inerciais (acelerómetros e xiroscopios) e técnicas de aprendizaxe automática. O sistema recolle datos en tempo real mediante microcontroladores, transmitíndoos a unha plataforma central para o seu procesamento e almacenamento. Ademais, desenvólvese unha aplicación móbil Android que permite aos usuarios visualizar os resultados, capturar vídeo sincronizado cos datos dos sensores e facilitar a etiquetaxe dos golpes para o adestramento dos modelos. O obxectivo principal é crear unha solución accesible, precisa e escalable para xogadores casuais e semiprofesionais, permitindo unha análise detallada dos movementos deportivos sen a necesidade de equipos complexos
ou custosos.
[Abstract]: This project focuses on the development of an innovative system for monitoring and classifying tennis strokes using inertial sensors (accelerometers and gyroscopes) and machine learning techniques. The system collects real-time data through microcontrollers and transmits it to a central platform for processing and storage. Additionally, an Android mobile application is developed to allow users to visualize results, capture video synchronized with sensor data, and facilitate stroke labelling for model training. The main goal is to create an accessible, accurate, and scalable solution for casual and semi-professional players, enabling detailed analysis of sports movements without the need for complex or expensive equipment.
[Abstract]: This project focuses on the development of an innovative system for monitoring and classifying tennis strokes using inertial sensors (accelerometers and gyroscopes) and machine learning techniques. The system collects real-time data through microcontrollers and transmits it to a central platform for processing and storage. Additionally, an Android mobile application is developed to allow users to visualize results, capture video synchronized with sensor data, and facilitate stroke labelling for model training. The main goal is to create an accessible, accurate, and scalable solution for casual and semi-professional players, enabling detailed analysis of sports movements without the need for complex or expensive equipment.
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Keywords
Clasificación de golpes de tenis Sensores inerciais Aprendizaxe automática Monitorización en tempo real Micro-controladores Aplicación Android Análise de movementos deportivos Sincronización de datos de sensores Tecnoloxía portátil Etiquetaxe de datos Tennis stroke classification Inertial sensors Machine learning Real-time monitoring Microcontrollers Android application Sports movement analysis Sensor data synchronization Wearable technology Data labeling
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Attribution 4.0 International







