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Author (up) Miarka, B.; Sterkowicz-Przybycien, K.; Fukuda, D.H. url  doi
openurl 
  Title Evaluation of Sex-Specific Movement Patterns in Judo Using Probabilistic Neural Networks Type Journal Article
  Year 2016 Publication Motor Control Abbreviated Journal Motor Control  
  Volume Issue Pages 1-29  
  Keywords Judo; Martial Arts and Statistics.; Motor Control; Task Performance and Analysis  
  Abstract The purpose of the present study was to create a probabilistic neural network (PNN) to clarify the understanding of movement patterns in international judo competitions by gender. Analysis of 773 male and 638 female bouts was utilized to identify movements during the approach, gripping, attack (including biomechanical designations), groundwork, defense, and pause phases. PNN and chi2 tests modeled and compared frequencies (p</=0.05). Women (mean[interquartile range]: 9.9[4;14]) attacked more than men (7.0[3;10]) while attempting a greater number of arm/leg lever (women: 2.7[1,6]; men: 4.0[0;4]) and trunk/leg lever (women: 0.8[0;1]; men: 2.4[0;4]) techniques, but fewer maximal length moment arm techniques (women: 0.7[0;1]; men: 1.0[0;2]). Male athletes displayed one-handed gripping of the back and sleeve, while female executed a greater number of groundwork techniques. An optimized PNN model, using patterns from the gripping, attack, groundwork, and pause phases, produced an overall prediction accuracy of 76% for discrimination between men and women.  
  Address 3 Institute of Exercise Physiology and Wellness, University Central Florida, Orlando, Florida  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1087-1640 ISBN Medium  
  Area Expedition Conference  
  Notes PMID:27736312 Approved no  
  Call Number JSP @ lw @ Serial 101  
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