Scoring accuracy of automated sleep staging from a bipolar electroocular recording compared to manual scoring by multiple raters

Abstract Objectives Electroencephalography (EEG) assessment in research and clinical studies is limited by the patient burden of multiple electrodes and the time needed to manually score records. The objective of our study was to investigate the accuracy of an automated sleep-staging algorithm which...

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Veröffentlicht in:Sleep medicine 2013-11, Vol.14 (11), p.1199-1207
Hauptverfasser: Stepnowsky, Carl, Levendowski, Daniel, Popovic, Djordje, Ayappa, Indu, Rapoport, David M
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container_end_page 1207
container_issue 11
container_start_page 1199
container_title Sleep medicine
container_volume 14
creator Stepnowsky, Carl
Levendowski, Daniel
Popovic, Djordje
Ayappa, Indu
Rapoport, David M
description Abstract Objectives Electroencephalography (EEG) assessment in research and clinical studies is limited by the patient burden of multiple electrodes and the time needed to manually score records. The objective of our study was to investigate the accuracy of an automated sleep-staging algorithm which is based on a single bipolar EEG signal. Methods Three raters each manually scored the polysomnographic (PSG) records from 44 patients referred for sleep evaluation. Twenty-one PSG records were scored by Rechtschaffen and Kales (R&K) criteria (group 1) and 23 PSGs were scored by American Academy of Sleep Medicine (AASM) 2007 criteria (group 2). Majority agreement was present in 98.4% of epochs and was used for comparison to automated scoring from a single EEG lead derived from the left and right electrooculogram. Results The κ coefficients for interrater manual scoring ranged from 0.46 to 0.89. The κ coefficient for the auto algorithm vs manual scoring by rater ranged from 0.42 to 0.63 and was 0.61 (group 1, κ = 0.61 and group 2, κ = 0.62) for majority agreement for all studies. The mean positive percent agreement across subjects and stages was 72.6%, approximately 80% for stages wake (78.3%), stage 2 sleep (N2) (80.9%), and stage 3 sleep (N3) (78.1%); the percentage slightly decreased to 73.2% for rapid eye movement (REM) sleep and dropped to 31.9% for stage 1 sleep (N1). Differences in agreement were observed based on raters, obstructive sleep apnea (OSA) severity, medications, and signal quality. Conclusions Our study demonstrated that automated scoring of sleep obtained from a single-channel of forehead EEG results in agreement to majority manual scoring are similar to results obtained from studies of manual interrater agreement. The benefit in assessing auto-staging accuracy with consensus agreement across multiple raters is most apparent in patients with OSA; additionally, assessing auto-staging accuracy limited disagreements in patients on medications and in those with compromised signal quality.
doi_str_mv 10.1016/j.sleep.2013.04.022
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The objective of our study was to investigate the accuracy of an automated sleep-staging algorithm which is based on a single bipolar EEG signal. Methods Three raters each manually scored the polysomnographic (PSG) records from 44 patients referred for sleep evaluation. Twenty-one PSG records were scored by Rechtschaffen and Kales (R&amp;K) criteria (group 1) and 23 PSGs were scored by American Academy of Sleep Medicine (AASM) 2007 criteria (group 2). Majority agreement was present in 98.4% of epochs and was used for comparison to automated scoring from a single EEG lead derived from the left and right electrooculogram. Results The κ coefficients for interrater manual scoring ranged from 0.46 to 0.89. The κ coefficient for the auto algorithm vs manual scoring by rater ranged from 0.42 to 0.63 and was 0.61 (group 1, κ = 0.61 and group 2, κ = 0.62) for majority agreement for all studies. The mean positive percent agreement across subjects and stages was 72.6%, approximately 80% for stages wake (78.3%), stage 2 sleep (N2) (80.9%), and stage 3 sleep (N3) (78.1%); the percentage slightly decreased to 73.2% for rapid eye movement (REM) sleep and dropped to 31.9% for stage 1 sleep (N1). Differences in agreement were observed based on raters, obstructive sleep apnea (OSA) severity, medications, and signal quality. Conclusions Our study demonstrated that automated scoring of sleep obtained from a single-channel of forehead EEG results in agreement to majority manual scoring are similar to results obtained from studies of manual interrater agreement. The benefit in assessing auto-staging accuracy with consensus agreement across multiple raters is most apparent in patients with OSA; additionally, assessing auto-staging accuracy limited disagreements in patients on medications and in those with compromised signal quality.</description><identifier>ISSN: 1389-9457</identifier><identifier>EISSN: 1878-5506</identifier><identifier>DOI: 10.1016/j.sleep.2013.04.022</identifier><identifier>PMID: 24047533</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>Adult ; Aged ; Algorithms ; Automatic sleep scoring ; Cross-Sectional Studies ; Electroencephalography ; Electroencephalography - methods ; Electroencephalography - standards ; Electroencephalography - statistics &amp; numerical data ; Electrooculography ; Electrooculography - methods ; Electrooculography - standards ; Electrooculography - statistics &amp; numerical data ; Female ; Forehead ; Humans ; Male ; Middle Aged ; Models, Neurological ; Neurology ; Observer Variation ; Polysomnography ; Polysomnography - methods ; Polysomnography - standards ; Polysomnography - statistics &amp; numerical data ; Reproducibility of Results ; Sleep Medicine ; Sleep stages ; Sleep Stages - physiology ; Validation studies ; Young Adult</subject><ispartof>Sleep medicine, 2013-11, Vol.14 (11), p.1199-1207</ispartof><rights>2013</rights><rights>Published by Elsevier B.V.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c525t-dcf219e947f1f44362f70d4ea884a4694183de0ffb64509ac83b2ad2914141023</citedby><cites>FETCH-LOGICAL-c525t-dcf219e947f1f44362f70d4ea884a4694183de0ffb64509ac83b2ad2914141023</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S1389945713002347$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65534</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24047533$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Stepnowsky, Carl</creatorcontrib><creatorcontrib>Levendowski, Daniel</creatorcontrib><creatorcontrib>Popovic, Djordje</creatorcontrib><creatorcontrib>Ayappa, Indu</creatorcontrib><creatorcontrib>Rapoport, David M</creatorcontrib><title>Scoring accuracy of automated sleep staging from a bipolar electroocular recording compared to manual scoring by multiple raters</title><title>Sleep medicine</title><addtitle>Sleep Med</addtitle><description>Abstract Objectives Electroencephalography (EEG) assessment in research and clinical studies is limited by the patient burden of multiple electrodes and the time needed to manually score records. The objective of our study was to investigate the accuracy of an automated sleep-staging algorithm which is based on a single bipolar EEG signal. Methods Three raters each manually scored the polysomnographic (PSG) records from 44 patients referred for sleep evaluation. Twenty-one PSG records were scored by Rechtschaffen and Kales (R&amp;K) criteria (group 1) and 23 PSGs were scored by American Academy of Sleep Medicine (AASM) 2007 criteria (group 2). Majority agreement was present in 98.4% of epochs and was used for comparison to automated scoring from a single EEG lead derived from the left and right electrooculogram. Results The κ coefficients for interrater manual scoring ranged from 0.46 to 0.89. The κ coefficient for the auto algorithm vs manual scoring by rater ranged from 0.42 to 0.63 and was 0.61 (group 1, κ = 0.61 and group 2, κ = 0.62) for majority agreement for all studies. The mean positive percent agreement across subjects and stages was 72.6%, approximately 80% for stages wake (78.3%), stage 2 sleep (N2) (80.9%), and stage 3 sleep (N3) (78.1%); the percentage slightly decreased to 73.2% for rapid eye movement (REM) sleep and dropped to 31.9% for stage 1 sleep (N1). Differences in agreement were observed based on raters, obstructive sleep apnea (OSA) severity, medications, and signal quality. Conclusions Our study demonstrated that automated scoring of sleep obtained from a single-channel of forehead EEG results in agreement to majority manual scoring are similar to results obtained from studies of manual interrater agreement. 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numerical data</topic><topic>Reproducibility of Results</topic><topic>Sleep Medicine</topic><topic>Sleep stages</topic><topic>Sleep Stages - physiology</topic><topic>Validation studies</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Stepnowsky, Carl</creatorcontrib><creatorcontrib>Levendowski, Daniel</creatorcontrib><creatorcontrib>Popovic, Djordje</creatorcontrib><creatorcontrib>Ayappa, Indu</creatorcontrib><creatorcontrib>Rapoport, David M</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Sleep medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Stepnowsky, Carl</au><au>Levendowski, Daniel</au><au>Popovic, Djordje</au><au>Ayappa, Indu</au><au>Rapoport, David M</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Scoring accuracy of automated sleep staging from a bipolar electroocular recording compared to manual scoring by multiple raters</atitle><jtitle>Sleep medicine</jtitle><addtitle>Sleep Med</addtitle><date>2013-11-01</date><risdate>2013</risdate><volume>14</volume><issue>11</issue><spage>1199</spage><epage>1207</epage><pages>1199-1207</pages><issn>1389-9457</issn><eissn>1878-5506</eissn><abstract>Abstract Objectives Electroencephalography (EEG) assessment in research and clinical studies is limited by the patient burden of multiple electrodes and the time needed to manually score records. The objective of our study was to investigate the accuracy of an automated sleep-staging algorithm which is based on a single bipolar EEG signal. Methods Three raters each manually scored the polysomnographic (PSG) records from 44 patients referred for sleep evaluation. Twenty-one PSG records were scored by Rechtschaffen and Kales (R&amp;K) criteria (group 1) and 23 PSGs were scored by American Academy of Sleep Medicine (AASM) 2007 criteria (group 2). Majority agreement was present in 98.4% of epochs and was used for comparison to automated scoring from a single EEG lead derived from the left and right electrooculogram. Results The κ coefficients for interrater manual scoring ranged from 0.46 to 0.89. The κ coefficient for the auto algorithm vs manual scoring by rater ranged from 0.42 to 0.63 and was 0.61 (group 1, κ = 0.61 and group 2, κ = 0.62) for majority agreement for all studies. The mean positive percent agreement across subjects and stages was 72.6%, approximately 80% for stages wake (78.3%), stage 2 sleep (N2) (80.9%), and stage 3 sleep (N3) (78.1%); the percentage slightly decreased to 73.2% for rapid eye movement (REM) sleep and dropped to 31.9% for stage 1 sleep (N1). Differences in agreement were observed based on raters, obstructive sleep apnea (OSA) severity, medications, and signal quality. Conclusions Our study demonstrated that automated scoring of sleep obtained from a single-channel of forehead EEG results in agreement to majority manual scoring are similar to results obtained from studies of manual interrater agreement. The benefit in assessing auto-staging accuracy with consensus agreement across multiple raters is most apparent in patients with OSA; additionally, assessing auto-staging accuracy limited disagreements in patients on medications and in those with compromised signal quality.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>24047533</pmid><doi>10.1016/j.sleep.2013.04.022</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record>
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source MEDLINE; Elsevier ScienceDirect Journals
subjects Adult
Aged
Algorithms
Automatic sleep scoring
Cross-Sectional Studies
Electroencephalography
Electroencephalography - methods
Electroencephalography - standards
Electroencephalography - statistics & numerical data
Electrooculography
Electrooculography - methods
Electrooculography - standards
Electrooculography - statistics & numerical data
Female
Forehead
Humans
Male
Middle Aged
Models, Neurological
Neurology
Observer Variation
Polysomnography
Polysomnography - methods
Polysomnography - standards
Polysomnography - statistics & numerical data
Reproducibility of Results
Sleep Medicine
Sleep stages
Sleep Stages - physiology
Validation studies
Young Adult
title Scoring accuracy of automated sleep staging from a bipolar electroocular recording compared to manual scoring by multiple raters
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