[Retracted] Analysis of Sports Injury Estimation Model Based on Mutation Fuzzy Neural Network

Wang, Dong; Yang, Jeng-Sheng

doi:10.1155/2021/3056428

Cited by 13 publications

(7 citation statements)

References 34 publications

(28 reference statements)

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“…In the field of national fitness, research focuses are mainly on fitness feedback, nutritious diet, and intelligent equipment. Wang and Yang [ 12 ] carried out research on the assessment of sports injury based on neural network. Novatchkov and other scholars [ 13 ] analyzed the training plan and training feedback of artificial intelligence strength training in the fitness process.…”

Section: Intelligent Sports: Rise Development and Applicationmentioning

confidence: 99%

Research on System Construction and Strategy of Intelligent Sports in the Implementation of National Fitness

Tang

Zan

Zhang

2022

Computational Intelligence and Neuroscience

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This paper studies the construction and development strategy of intelligent sports system in the context of Chinese National Fitness Program with methods of literature review and model construction. The research shows that there are four dilemmas in the implementation of intelligent sports in national fitness: data security, market monopoly, legal supervision, and product iteration. However, there are also three promoting factors in this regard, including policy guarantee, market demand, and industrial upgrading. Following the principles of scientificity, effectiveness, public welfare, and collaboration, this paper designs a system for intelligent sports in national fitness. The construction of the national fitness intelligent sports system mainly consists of four modules, including basic framework construction, function design, content design, and operation analysis. With the systematic analysis of the status quo of intelligent sports application in national fitness, this paper puts forward intelligent sports development strategies in the implementation of national fitness from four aspects: optimizing the top-level design of government, speeding up industrial transformation and upgrading, constructing market supervision mechanism, and establishing a talent training system.

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Section: Intelligent Sports: Rise Development and Applicationmentioning

confidence: 99%

Research on System Construction and Strategy of Intelligent Sports in the Implementation of National Fitness

Tang

Zan

Zhang

2022

Computational Intelligence and Neuroscience

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“…They found that the fuzzy neural network outperformed Bayesian and Lagrange models. However, this was a theoretical proposal using simulated data [ 51 ]. Another 2021 paper by Zhang et al proposed a grey neural network that inputs the results of n-grey models into a neural network for final prediction.…”

Section: Reviewmentioning

confidence: 99%

An Overview of Machine Learning Applications in Sports Injury Prediction

Amendolara,

Pfister,

Settelmayer

et al. 2023

Cureus

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Use injuries, i.e., injuries caused by repetitive strain on the body, represent a serious problem in athletics that has traditionally relied on historic datasets and human experience for prevention. Existing methodologies have been frustratingly slow at developing higher precision prevention practices. Technological advancements have permitted the emergence of artificial intelligence and machine learning (ML) as promising toolsets to enhance both injury mitigation and rehabilitation protocols. This article provides a comprehensive overview of recent advances in ML techniques as they have been applied to sports injury prediction and prevention. A comprehensive literature review was conducted searching PubMed/Medline, Institute of Electrical and Electronics Engineers (IEEE)/Institute of Engineering and Technology (IET), and ScienceDirect. Ovid Discovery and Google Scholar were used to provide additional aggregate results and a grey literature search. A focus was placed on papers published from 2017 to 2022. Algorithms of interest were limited to K-Nearest Neighbor (KNN), K-means, decision tree, random forest, gradient boosting and AdaBoost, and neural networks. A total of 42 original research papers were included, and their results were summarized. We conclude that given the current lack of open source, uniform data sets, as well as a reliance on dated regression models, no strong conclusions about the real-world efficacy of ML as it applies to sports injury prediction can be made. However, it is suggested that addressing these two issues will allow powerful, novel ML architectures to be deployed, thus rapidly advancing the state of this field, and providing validated clinical tools.

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“…They discovered that the fuzzy neural network performed much better than the Bayesian and Lagrange models. Having that, this was just a theoretical proposition that used simulated data [81]. In another research published in 2021, Zhang et al suggested a grey neural network.…”

Section: Fuzzy and Neural Networkmentioning

confidence: 99%

Injury Prediction in Sports using Artificial Intelligence Applications: A Brief Review

Kumar,

Reddy

et al. 2023

Journal of Robotics and Control

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Avoiding injuries in sports has always depended on historical records and human experience. This is despite using injuries being a major and unsolvable issue. The development of more precise preventative procedures using the now available approaches has been excruciatingly sluggish. The development of artificial intelligence (AI) and machine learning (ML) as potentially valuable procedures to improve damage prevention and recovery procedures has been made possible by technological advances that have made these areas more accessible. This article presents a detailed summary of ML approaches as they have been used to predict and anticipate sports injuries to this point in time. The research conducted over the last five years has been collated, and its results have been untaken. Assuming the present absence of accessible sources, standardized statistics, and a dependence on obsolete deterioration prototypes, it is impossible to draw any definitive conclusions regarding the real-world effectiveness of machine learning in terms of its application to the prediction of sports injuries. However, it has been hypothesized that resolving these two problems would make it possible to deploy innovative, strong machine-learning architectures, which will hasten the process of increasing the state of this area while also offering proven clinical tools.

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[Retracted] Analysis of Sports Injury Estimation Model Based on Mutation Fuzzy Neural Network

Cited by 13 publications

References 34 publications

Research on System Construction and Strategy of Intelligent Sports in the Implementation of National Fitness

Research on System Construction and Strategy of Intelligent Sports in the Implementation of National Fitness

An Overview of Machine Learning Applications in Sports Injury Prediction

Injury Prediction in Sports using Artificial Intelligence Applications: A Brief Review

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