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Wavelet-Based Multiscale Decomposition Algorithm for Trajectory Capture of Tennis Serves.

Shiguang Wang1, Yaozhen Cui2

  • 1Department of Physical Education, Yulin University, Yulin 719000, China.

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Summary
This summary is machine-generated.

This study introduces a novel method using multidimensional wavelet segmentation to capture tennis ball trajectories. This technique effectively guides tennis serving actions for improved performance.

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Area of Science:

  • Sports Science
  • Biomechanics
  • Signal Processing

Background:

  • Tennis is a growing recreational sport with increasing participation across all age groups.
  • The tennis serve is a fundamental yet challenging aspect of the game, crucial for controlling play.
  • Optimizing serving technique is vital for both recreational and professional tennis players.

Purpose of the Study:

  • To develop and evaluate a method for accurately capturing tennis ball trajectories.
  • To provide an effective reference for analyzing and improving tennis serving actions.
  • To leverage advanced signal processing for sports performance enhancement.

Main Methods:

  • Utilizing multidimensional wavelet segmentation for trajectory analysis.
  • Applying the method to capture the dynamic path of a tennis ball during a serve.
  • Developing algorithms for real-time or post-action analysis of serve trajectories.

Main Results:

  • The proposed multidimensional wavelet segmentation method demonstrated a good trajectory capturing effect.
  • The technique showed effectiveness in correcting and guiding tennis serving actions.
  • Quantitative analysis of captured trajectories can provide actionable feedback for players.

Conclusions:

  • Multidimensional wavelet segmentation offers a promising approach for analyzing tennis serve dynamics.
  • This method can serve as a valuable tool for coaching and player development in tennis.
  • Further research can explore real-time applications and integration with other biomechanical analyses.