Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Different Dual-Task Paradigm Reduce Postural Control Ability and Dynamic Stability of Healthy Young Adults during Stair Descent.

Applied bionics and biomechanics·2024
Same author

Selective binding of phorbol esters and diacylglycerol by individual C1 domains of the PKD family.

The Biochemical journal·2007
Same author

[Investigation and analysis of China residents' environmental conservation desire].

Ying yong sheng tai xue bao = The journal of applied ecology·2007
Same author

[Analysis and identification of sea cucumber and products].

Guang pu xue yu guang pu fen xi = Guang pu·2007
Same author

Systematic identification of C. elegans miRISC proteins, miRNAs, and mRNA targets by their interactions with GW182 proteins AIN-1 and AIN-2.

Molecular cell·2007
Same author

HDAC inhibitor PCI-24781 decreases RAD51 expression and inhibits homologous recombination.

Proceedings of the National Academy of Sciences of the United States of America·2007

Related Experiment Video

Updated: Sep 6, 2025

Asymmetric Walkway: A Novel Behavioral Assay for Studying Asymmetric Locomotion
08:19

Asymmetric Walkway: A Novel Behavioral Assay for Studying Asymmetric Locomotion

Published on: January 15, 2016

8.9K

Wushu Routine Movement and Diagnosis Based on Deep Learning and Symmetric Difference Algorithm.

Shifang Yan1, Jun Chen2, Hai Huang2

  • 1Department of Wushu, Hebei Sport University, Shijiazhuang 050000, Hebei, China.

Computational Intelligence and Neuroscience
|June 27, 2022
PubMed
Summary

Analyzing Wushu routines using deep learning and symmetric difference algorithms provides quantitative insights for athletes. Wushu routine quality significantly impacts competition performance, with an influence index of 4.3.

More Related Videos

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
06:49

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Published on: December 11, 2015

9.0K
Visualizing Motion Patterns in Acupuncture Manipulation
08:18

Visualizing Motion Patterns in Acupuncture Manipulation

Published on: July 16, 2016

8.8K

Related Experiment Videos

Last Updated: Sep 6, 2025

Asymmetric Walkway: A Novel Behavioral Assay for Studying Asymmetric Locomotion
08:19

Asymmetric Walkway: A Novel Behavioral Assay for Studying Asymmetric Locomotion

Published on: January 15, 2016

8.9K
Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
06:49

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Published on: December 11, 2015

9.0K
Visualizing Motion Patterns in Acupuncture Manipulation
08:18

Visualizing Motion Patterns in Acupuncture Manipulation

Published on: July 16, 2016

8.8K

Area of Science:

  • Sports Science
  • Artificial Intelligence
  • Algorithm Analysis

Background:

  • Wushu is a traditional Chinese martial art and popular sport.
  • Increasingly competitive Wushu requires precise routine analysis for performance enhancement.
  • Traditional analysis methods lack quantitative indicators for technical training.

Purpose of the Study:

  • To investigate the analysis and diagnosis of Wushu routines.
  • To apply deep learning and symmetric difference algorithms for Wushu routine assessment.
  • To identify key factors influencing Wushu athletes' competition performance.

Main Methods:

  • Utilized deep learning algorithms for complex pattern recognition in Wushu movements.
  • Employed the symmetric difference algorithm to quantify routine accuracy and identify deviations.
  • Integrated both algorithms to provide a comprehensive analysis of Wushu routines.

Main Results:

  • The study established a novel method for quantitative analysis of Wushu routines.
  • Deep learning and symmetric difference algorithms effectively diagnosed technical aspects of Wushu movements.
  • Wushu routine proficiency was identified as the most critical factor for competition success.

Conclusions:

  • The level of Wushu routines has the greatest influence on competition performance.
  • The developed approach offers valuable quantitative data for Wushu training and coaching.
  • Technological integration in Wushu analysis enhances athlete development and competitive outcomes.