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Identification Of Movement Strategies In Vertical Jumps

Authors: 

Chris Richter, Brendan Marshall, Noel O'Connor, Kieran Moran

Publication Type: 
Refereed Conference Meeting Proceeding
Abstract: 
The primary aim of this study is to compare the ability of three commonly used clustering techniques to identify movement strategies within countermovement jumps. A secondary aim is to interpret the identified movement strategies. A hierarchical, k-means using non- and normalized subject scores and an Expectation-Maximization approach using normalized subject scores were examined. The ability to identify movement strategies was measured using the r2-value of a regression model to describe jump height. Clusters of the best clustering solution were examined for differences. Hierarchical clustering utilizing normalized subject scores to generate 4 clusters appears to be the most suitable technique. The generated clusters demonstrated clear defining characteristics.
Conference Name: 
Symposium of the International Society of Biomechanics in Sports.
Proceedings: 
The 32nd Conference of the International Society of Biomechanics in Sports
Digital Object Identifer (DOI): 
10.NA
Publication Date: 
09/04/2014
Conference Location: 
United States of America
Research Group: 
Institution: 
Dublin City University (DCU)
Open access repository: 
Yes