Document Detail

Clustering vertical ground reaction force curves produced during countermovement jumps.
MedLine Citation:
PMID:  24845694     Owner:  NLM     Status:  Publisher    
The aim of this study is to assess and compare the performance of commonly used hierarchical, partitional (k-means) and Gaussian model-based (Expectation-Maximization algorithm) clustering techniques to appropriately identify subgroup patterns within vertical ground reaction force data, using a continuous waveform analysis. In addition, we also compared the performance across each technique using normalized and non-normalization input scores. Both generated and real data (one hundred and twenty two vertical jumps) were analyzed. The performance of each cluster technique was measured by assessing the ability to explain variances in jump height using a stepwise regression analysis. Only k-means (normalized scores; 82%) and hierarchical clustering (normalized scores; 85%) were able to extend the ability to describe variances in jump height beyond that achieved using the group analysis (i.e. one cluster; 78%). Further, our findings strongly indicate the need to normalize the input data (similarity measure) when clustering. In contrast to the group analysis, the subgroup analysis was able to identify cluster specific phases of variance, which improved the ability to explain variances in jump height, due to the identification of cluster specific predictor variables. Our findings therefore highlight the benefit of performing a subgroup analysis and may explain, at least in part, the contrasting findings between previous studies that used a single group level of analysis.
Chris Richter; Noel E O׳Connor; Brendan Marshall; Kieran Moran
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2014-4-26
Journal Detail:
Title:  Journal of biomechanics     Volume:  -     ISSN:  1873-2380     ISO Abbreviation:  J Biomech     Publication Date:  2014 Apr 
Date Detail:
Created Date:  2014-5-21     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0157375     Medline TA:  J Biomech     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2014 Elsevier Ltd. All rights reserved.
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