Linked Life Data

1376663

Source:http://linkedlifedata.com/resource/pubmed/id/1376663

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
1992-7-22
pubmed:abstractText
Frequency and amplitude characteristics of the clinical (waking) electroencephalogram (EEG) can be diagnostically useful in neuronal degenerative disorders such as Alzheimer's or other cortical dementias. However, interpretation of the clinical EEG may be limited by many factors, including movement and muscle artifacts and uncontrolled variations along the alert/drowsy continuum. Moreover, the clinical EEG involves subjective judgement by experts whose opinions often differ. In an effort to address these problems, we have developed a computer-automated technology that examines the digitized, all-night sleep EEG for frequency and amplitude characteristics of potential diagnostic relevance to Alzheimer's dementia. Robust time series analysis techniques and a modified power spectral analysis (Z-spectra) are used to suppress artifactual information and to automatically select samples of tonic REM sleep EEG. The spectra (amplitude vs. frequency relationship) of this specific EEG state is then assessed for diagnostically relevant information.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jul
pubmed:issn
0013-4694
pubmed:author
pubmed:issnType
Print
pubmed:volume
83
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
24-35
pubmed:dateRevised
2008-9-9
pubmed:meshHeading
pubmed:year
1992
pubmed:articleTitle
Quantitative analysis of the EEG during tonic REM sleep--methodology.
pubmed:affiliation
Department of Psychiatry and Behavioural Sciences, University of Washington, Seattle 98195.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, U.S. Gov't, Non-P.H.S.