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Sports Injury Identification Method Based on Machine Learning Model.

Zexu Liu1, Jun Zhang1, Di Wu1

  • 1School of Sports Training, Wuhan Sports University, Wuhan 430000, Hubei, China.

Computational Intelligence and Neuroscience
|August 18, 2022
PubMed
Summary
This summary is machine-generated.

This study analyzed elite rhythmic gymnastics injuries using machine learning to identify high-risk movements. Female vaulting poses the greatest acute sports injury risk, highlighting areas for targeted prevention strategies.

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Area of Science:

  • Sports Medicine
  • Biomechanics
  • Data Science in Sports

Background:

  • Intensified international sports competition drives increased training loads, leading to more severe sports injuries.
  • Sports injuries impede athlete development and necessitate effective prevention, treatment, and rehabilitation strategies.
  • Machine learning offers advanced capabilities for analyzing complex datasets and identifying patterns in sports injuries.

Purpose of the Study:

  • To investigate the injury characteristics and causes in elite rhythmic gymnasts.
  • To evaluate the injury risk of key athletes using scientific indicators.
  • To provide references for sports injury prevention and rehabilitation programs.

Main Methods:

  • Investigated injury status of elite rhythmic gymnasts.
  • Applied scientific qualitative and quantitative indicators.
  • Utilized machine learning for risk evaluation based on project characteristics, athlete factors, and injury data.

Main Results:

  • Identified specific injury characteristics and causes within rhythmic gymnastics.
  • Evaluated injury risk for key athletes.
  • Female vaulting demonstrated the highest acute sports injury risk, with scores ranging from 179.62 to 365.8 across five risk categories.

Conclusions:

  • The study provides valuable insights into rhythmic gymnastics injuries.
  • Machine learning effectively evaluated injury risk, identifying female vaulting as a high-risk activity.
  • Findings support the development of targeted injury prevention and rehabilitation strategies for rhythmic gymnasts.