Linked Life Data

21096830

Source:http://linkedlifedata.com/resource/pubmed/id/21096830

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2010-11-24
pubmed:abstractText
In this manuscript we present an overview of novel signal processing techniques developed by our group to reduce scoring time in the assessment of the severity of sleep-related breathing disorders in heart failure patients and to detect sleep/wake fluctuations during periodic breathing. Besides describing these methods, we present the results of validation experiments. Our work shows that novel signal processing techniques can reduce costs and resources needed to screen the patients and can provide relevant information for better understanding the role of wake/sleep transitions in the development and maintenance of breathing disorders.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1557-170X
pubmed:author
pubmed:issnType
Print
pubmed:volume
2010
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
3571-4
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Assessing the severity and improving the understanding of sleep-related breathing disorders in heart failure patients.
pubmed:affiliation
Department of Biomedical Engineering, S. Maugeri Foundation, Montescano, Italy. giandomenico.pinna@fsm.it
pubmed:publicationType
Journal Article