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Artificial Intelligence Technology in Basketball Training Action Recognition.

Yao Cheng1, Xiaojun Liang2,3, Yi Xu4

  • 1Shaoxing University Yuanpei College, Shaoxing, China.

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|July 14, 2022
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) enhances basketball training through intelligent movement detection. The back propagation artificial neural network (ANN) algorithm achieved over 95% accuracy in recognizing key basketball actions.

Keywords:
accuracyartificial neural networkbasketball trainingrecallsomatosensory motion gesture recognition

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Area of Science:

  • Sports Science
  • Artificial Intelligence
  • Biomechanical Analysis

Background:

  • Basketball training relies on precise movement analysis for skill development.
  • Traditional methods for assessing athlete movements can be subjective and time-consuming.
  • The integration of AI offers potential for objective and efficient movement detection.

Purpose of the Study:

  • To investigate the efficacy of artificial intelligence (AI) for intelligent movement detection in basketball training.
  • To analyze somatosensory gesture recognition theory as a foundation for AI-driven movement analysis.
  • To compare the performance of four distinct algorithms in recognizing athletes' limb movements.

Main Methods:

  • Signal denoising and normalization of collected movement data.
  • Application of Decision Tree (DT), Naive Bayes (NB), Support Vector Machine (SVM), and Artificial Neural Network (ANN) algorithms.
  • Comparative analysis of algorithm accuracy and recall rates for limb movement detection.

Main Results:

  • The back propagation Artificial Neural Network (BP ANN) demonstrated superior performance in action recognition.
  • High accuracy (approx. 93.3%) and recall (approx. 93.3%) were achieved for upper limb movements.
  • Exceptional accuracy (approx. 99.4%) and recall (approx. 99.4%) were recorded for lower limb movements.
  • Over 95% recognition rate for core actions (catching, passing, dribbling, shooting) with an average accuracy of ~98.95%.

Conclusions:

  • AI, particularly the BP ANN algorithm, offers a highly accurate and efficient method for detecting basketball movements.
  • The developed intelligent system can aid coaches in refining training programs and improving athlete skill levels.
  • This technology provides objective feedback for enhancing basketball player performance.