Linked Life Data

10513122

Source:http://linkedlifedata.com/resource/pubmed/id/10513122

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
10
pubmed:dateCreated
1999-12-9
pubmed:abstractText
Information management for critical care monitoring is still a very difficult task. Medical staff is often overwhelmed by the amount of data provided by the increased number of specific monitoring devices and instrumentation, and the lack of an effective automated system. Specifically, a basic task such as arrhythmia detection still produce an important amount of undesirable alarms, due in part to the mechanistic approach of current monitoring systems. In this work, multisensor and multisource data fusion schemes to improve atrial and ventricular activity detection in critical care environments are presented. Applications of these schemes are quantitatively evaluated and compared with current methods, showing the potential advantages of data fusion techniques for event detection in noise corrupted signals.
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
0018-9294
pubmed:author
pubmed:issnType
Print
pubmed:volume
46
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1186-90
pubmed:dateRevised
2009-11-18
pubmed:meshHeading
pubmed:year
1999
pubmed:articleTitle
Multisensor fusion for atrial and ventricular activity detection in coronary care monitoring.
pubmed:affiliation
Laboratoire Traitement du Signal et de l'Image, Universite de Rennes, France. Alfredo.Hernandez@univ-rennes1.fr
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't