Two-group classification of patients with obstructive sleep apnea based on analysis of brain recurrence

Highlights • The severity of obstructive sleep apnea (OSA) was directly reflected in the sleep EEG. • Binary classification of patients with OSA (mild or moderate) was achieved by analyzing the EEG from one derivation. • Analysis of brain recurrence is an effective algorithmic technique for extracti...

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Bibliographic Details
Published inClinical neurophysiology Vol. 125; no. 6; pp. 1174 - 1181
Main Authors Kim, Paul Y, McCarty, David E, Wang, Lei, Frilot, Clifton, Chesson, Andrew L, Marino, Andrew A
Format Journal Article
LanguageEnglish
Published Netherlands Elsevier Ireland Ltd 01.06.2014
Subjects
Algorithms
Area Under Curve
Biomarkers
Brain recurrence analysis
Cohort Studies
Electroencephalography
Female
Humans
Linear discrimination analysis
Male
Middle Aged
Neurology
Obstructive sleep apnea
Polysomnography - methods
ROC Curve
Sleep Apnea, Obstructive - classification
Sleep Apnea, Obstructive - complications
Sleep Apnea, Obstructive - diagnosis
Sleep Apnea, Obstructive - physiopathology
Sleep Deprivation - complications
Sleep Deprivation - diagnosis
Sleep Deprivation - physiopathology
Sleep depth
Sleep fragmentation
Sleep Stages - physiology
Biomarkers
Sleep fragmentation
Linear discrimination analysis
Brain recurrence analysis
Obstructive sleep apnea
Sleep depth
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Summary:Highlights • The severity of obstructive sleep apnea (OSA) was directly reflected in the sleep EEG. • Binary classification of patients with OSA (mild or moderate) was achieved by analyzing the EEG from one derivation. • Analysis of brain recurrence is an effective algorithmic technique for extracting useful diagnostic information regarding OSA from the EEG.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1388-2457
1872-8952
DOI:10.1016/j.clinph.2013.11.002