Linked Life Data

19964990

Source:http://linkedlifedata.com/resource/pubmed/id/19964990

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2009-12-7
pubmed:abstractText
Surrogates are commonly used to test a particular hypothesis on time series. The parameter commonly used in the literature to test these hypotheses is the z score. The z score assumes that the distribution of the statistics obtained on the surrogates is Gaussian. In this paper, we propose the use of a more general parameter than the z score that will also work in the case of non-Gaussian distribution of the statistics. We also derive a statistical test, based on the fitting of the distribution of the surrogate measure profile, in order to test the initial hypothesis. We validate the proposed approach on both synthetic signals and real uterine EMG signals by using the nonlinear correlation coefficient as initial statistic. We further show that this corrected nonlinear correlation coefficient can discriminate between pregnancy contractions and labor in a monkey, but the uncorrected nonlinear correlation coefficient cannot. This makes the corrected nonlinear correlation coefficient a promising candidate in a future application for preterm labor prediction in humans.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1557-170X
pubmed:author
pubmed:issnType
Print
pubmed:volume
2009
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
3477-80
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Nonlinearity testing in the case of non Gaussian surrogates, applied to improving analysis of synchronicity in uterine contraction.
pubmed:affiliation
School of Science and Engineering, Reykjavik University, Reykjavik, 103 Iceland. jeremy@ru.is
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't