The variance needed to accurately describe jump height from vertical ground reaction force data.

Abstract:

:In functional principal component analysis (fPCA) a threshold is chosen to define the number of retained principal components, which corresponds to the amount of preserved information. A variety of thresholds have been used in previous studies and the chosen threshold is often not evaluated. The aim of this study is to identify the optimal threshold that preserves the information needed to describe a jump height accurately utilizing vertical ground reaction force (vGRF) curves. To find an optimal threshold, a neural network was used to predict jump height from vGRF curve measures generated using different fPCA thresholds. The findings indicate that a threshold from 99% to 99.9% (6-11 principal components) is optimal for describing jump height, as these thresholds generated significantly lower jump height prediction errors than other thresholds.

journal_name

J Appl Biomech

authors

Richter C,McGuinness K,O'Connor NE,Moran K

doi

10.1123/jab.2013-0313

subject

Has Abstract

pub_date

2014-12-01 00:00:00

pages

732-6

issue

6

eissn

1065-8483

issn

1543-2688

pii

2013-0313

journal_volume

30

pub_type

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