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The development of a machine learning/augmented reality immersive training system for performance monitoring in athletes

Published: 11 July 2022 Publication History
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  • Abstract

    As technology advances in computer graphics, augmented reality has become an increasingly popular tool for entertainment and learning purposes, especially in the sports sector. Examples can be found in different sports such as rugby, baseball, and soccer, among others. This paper proposes an AR-based training system that can be used as a self-learning tool to improve athletes' decision-making process. The system will contain a feedback module that will offer users challenges and, based on user performance, it will be possible to track and assess athletes' progress. The user will learn about their limits during the challenges while practicing different activities. As the user becomes physically fatigued, a score will be shown for performance improvement. Therefore, this work aims to develop a performance attenuation monitoring system for athletes, consequently, contributing to mental and physical improvement of athletes' performance related to the sport practiced.

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    1. The development of a machine learning/augmented reality immersive training system for performance monitoring in athletes

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      cover image ACM Conferences
      MMVE '22: Proceedings of the 14th International Workshop on Immersive Mixed and Virtual Environment Systems
      June 2022
      59 pages
      ISBN:9781450393829
      DOI:10.1145/3534086
      • General Chair:
      • Conor Keighrey
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Published: 11 July 2022

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      Author Tags

      1. augmented reality
      2. human-machine interaction
      3. performance attenuation
      4. sports training

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      Overall Acceptance Rate 26 of 44 submissions, 59%

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