15276236

Source:http://linkedlifedata.com/resource/pubmed/id/15276236

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Predicate	Object
rdf:type	pubmed:Citation
lifeskim:mentions	umls-concept:C0034897, umls-concept:C0037313, umls-concept:C0037315, umls-concept:C0086418, umls-concept:C0936012
pubmed:issue	2
pubmed:dateCreated	2004-7-27
pubmed:abstractText	The aim of this study is to elucidate whether the results of recurrence quantification analysis (RQA) of sleep EEGs in sleep apnea syndrome are valuable for analyzing sleep EEGs in sleep apnea syndrome. We investigated the ability of RQA to discriminate sleep stages and to characterize the different behaviors of sleep EEGs in sleep apnea syndrome. RQA was applied to EEG signals during sleep stages 1, 2, slow wave sleep (SWS), REM and the stage 'awake.' The sleep EEG signals were obtained from the MIT-BIH polysomnographic database. To examine the differences in the RQA measures for all sleep stages, one-way analysis of variance (ANOVA) and post hoc analysis were performed. From the results, all sleep stages could be distinctly discriminated by means of the RQA measure of %RATIO. We observed that stage 1 and REM had fewer recurrences, and that stage 2 was more autocorrelated than the other stages. The different dynamic behaviors of wakefulness and sleep EEG were also observed. Of significant interest was the observation that RQA was able to distinguish stage 1 from REM. In conclusion, we suggest that the information obtained from RQA of sleep EEGs in sleep apnea syndrome is valuable for its analysis, and that RQA constitutes a useful tool for analyzing sleep EEGs in subjects with sleep apnea syndrome.
pubmed:language	eng
pubmed:journal	http://linkedlifedata.com/resource/pubmed/journal/7600130
pubmed:citationSubset	IM
pubmed:status	MEDLINE
pubmed:month	Aug
pubmed:issn	0304-3940
pubmed:author	pubmed-author:KimSun ISI, pubmed-author:LeeDoo-SooDS, pubmed-author:SongIn-HoIH
pubmed:issnType	Print
pubmed:day	12
pubmed:volume	366
pubmed:owner	NLM
pubmed:authorsComplete	Y
pubmed:pagination	148-53
pubmed:dateRevised	2006-11-15
pubmed:meshHeading	pubmed-meshheading:15276236-Computing Methodologies, pubmed-meshheading:15276236-Electroencephalography, pubmed-meshheading:15276236-Humans, pubmed-meshheading:15276236-Sleep, pubmed-meshheading:15276236-Sleep Apnea Syndromes
pubmed:year	2004
pubmed:articleTitle	Recurrence quantification analysis of sleep electoencephalogram in sleep apnea syndrome in humans.
pubmed:affiliation	Department of Electrical and Computer Engineering, Hanyang University, 17 Haengdang-dong, Seongdong-gu, Seoul 133-791, South Korea.
pubmed:publicationType	Journal Article, Research Support, Non-U.S. Gov't