Linked Life Data

1455130

Source:http://linkedlifedata.com/resource/pubmed/id/1455130

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
1993-1-6
pubmed:abstractText
The purpose of this study was to develop and validate automatic scoring methods to distinguish sleep from wakefulness based on wrist activity. Forty-one subjects (18 normals and 23 with sleep or psychiatric disorders) wore a wrist actigraph during overnight polysomnography. In a randomly selected subsample of 20 subjects, candidate sleep/wake prediction algorithms were iteratively optimized against standard sleep/wake scores. The optimal algorithms obtained for various data collection epoch lengths were then prospectively tested on the remaining 21 subjects. The final algorithms correctly distinguished sleep from wakefulness approximately 88% of the time. Actigraphic sleep percentage and sleep latency estimates correlated 0.82 and 0.90, respectively, with corresponding parameters scored from the polysomnogram (p < 0.0001). Automatic scoring of wrist activity provides valuable information about sleep and wakefulness that could be useful in both clinical and research applications.
pubmed:grant
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
0161-8105
pubmed:author
pubmed:issnType
Print
pubmed:volume
15
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
461-9
pubmed:dateRevised
2009-1-29
pubmed:meshHeading
pubmed:year
1992
pubmed:articleTitle
Automatic sleep/wake identification from wrist activity.
pubmed:affiliation
Department of Psychiatry, University of California, San Diego.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, U.S. Gov't, Non-P.H.S.