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Related Experiment Video

Updated: Aug 27, 2025

Movement Retraining using Real-time Feedback of Performance
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Evaluation Method of Public Physical Training Quality Based on Global Topology Optimization Deep Learning Model.

JingMing Yan1

  • 1School of Culture and Media, Xinhua University, Hefei 230088, China.

Journal of Environmental and Public Health
|September 26, 2022
PubMed
Summary

This study introduces a novel deep learning model for public sports training quality evaluation. The method enhances accuracy by using global topology optimization to analyze comprehensive training indicators.

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Area of Science:

  • Sports Science
  • Artificial Intelligence
  • Data Analysis

Background:

  • Current public sports training quality evaluations lack comprehensive indicators, leading to inaccuracies.
  • Existing methods may not fully capture the nuances of training effectiveness.

Purpose of the Study:

  • To develop an advanced quality evaluation method for public sports training.
  • To improve the accuracy and reliability of public sports training assessments.

Main Methods:

  • Utilizing a deep learning model integrated with global topology optimization.
  • Determining human coordinate points and extracting quality evaluation data.
  • Quantifying indicators, constructing evaluation matrices, and calculating index weights.

Main Results:

  • The proposed method effectively preprocesses evaluation index sets.
  • The global topology optimization deep learning model identifies optimal fitness values.
  • The system successfully inputs evaluation indices and outputs quality assessment results.

Conclusions:

  • The developed evaluation method significantly improves the accuracy of public sports training quality assessment.
  • The approach is demonstrated to be feasible and effective for practical application.