Artificial intelligence and data processing in injury diagnosis and prevention in competitive sports: A literature review

Poulios, Panagiotis; Serlis, Athanasios; Groumpos, Peter P.; Gliatis, Ioannis

doi:10.15406/mojor.2021.13.00544

Cited by 1 publication

(1 citation statement)

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“…AI offers a fascinating new viewpoint on injury risk and team sports performance prediction. Another literature study [8] covers AI in sports medicine, data processing, injury diagnosis, and prevention in competitive sports. Models and approaches in the literature study include fuzzy sets, ANN, Markov process, and other models such as Bayesian theory and multi-dimensional models groups.…”

Section: Analysis Of Related Surveys and Taxanomiesmentioning

confidence: 99%

A Survey of Evolving Performance Analysis Technologies, Algorithms and Models for Sports

Subramaniam,

Shankar,

Zazali

et al. 2023

IJACSA

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The emergence and extensive development and deployment of Industrial Revolution 4.0 have distinctly transformed the methodologies of sports performance monitoring. Consequently, there has been an increase in the emergence of new and adapted technologies in various areas of sports, such as competition analysis, player performance analysis and many others. There are rich and heterogeneous sports performance analysis technologies, algorithms and frameworks which provide constant basis for elevating new horizons of sports technologies. Thus, this paper aims to encompass significant findings that will provide a comprehensive survey in this area. Previous surveys have extensively focused on various methodologies of sports performance analysis, sport-specific analysis and other technology revolving around sports performance analysis. However, most of the focus is largely on training and competition performances and not off-field. The objective of this paper is to understand the current research trends, challenges and future directions of dynamically evolving technology embedded in the world of sports. This survey aims at contributing to this rich repository but with a new focus element of off-field that researches the connection between the athlete, the sports aspect of their life, the non-sport aspect and the methodologies of sports performance analysis. In addition, the exponential growth of Artificial Intelligence (AI) as a base for sports performance analysis systems and platforms is analysed extensively. This paper also presents a comprehensive classification of athlete performance analysis using algorithm tools and sports performance platforms and systems. Subsequently, the detailed analysis of this taxonomy has enabled the identification and detailed analysis of open issues and future directions.

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Section: Analysis Of Related Surveys and Taxanomiesmentioning

confidence: 99%