Linked Life Data

14563086

Source:http://linkedlifedata.com/resource/pubmed/id/14563086

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2003-10-17
pubmed:abstractText
The development of suitable techniques for quantifying mechanical and electrophysiological aspects of uterine contractions has been an active area of research. The uterus is a physiological system consisting of a large number of interacting muscle cells. The activity of these cells evolves with time, a trait characteristic of a dynamical system. While such complex physiological systems are non-linear by their very nature, whether this non-linearity is exhibited in the external recording is far from trivial. Traditional techniques such as spectral analysis have been used in the past, but these techniques implicitly assume that the process generating the contractions is linear and hence may be biased. In this tutorial review, a systematic approach using a hierarchy of surrogate algorithms is used to determine the nature of the process generating the contractions produced during labor. The results reveal that uterine contractions are probably generated by non-linear processes. The contraction segments were obtained through simultaneous recordings of the electrical and magnetic signals corresponding to the electrophysiological activity of the uterus and then analyzed. The electrical activity was recorded by placement of non-invasive electrodes onto the maternal abdomen and magnetic activity was recorded non-invasively using a superconducting quantum interference device (SQUID).
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jul
pubmed:issn
1476-7058
pubmed:author
pubmed:issnType
Print
pubmed:volume
14
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
8-21
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
Analysis of uterine contractions: a dynamical approach.
pubmed:affiliation
Center on Aging, University of Arkansas for Medical Sciences, Little Rock, Arkansas 72205, USA.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Review