Computer based sleep staging: Challenges for the future

Studies have shown that patients suffering from sleep deprivation have a risk for hypertension, diabetes and depression that is higher than normal sleepers. Treatment for all these problems requires accurate analysis of the sleep stages and patterns in the polysomnographic signals collected in overn...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Hamida, Sana Tmar-Ben, Ahmed, Beena
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 285
container_issue
container_start_page 280
container_title
container_volume
creator Hamida, Sana Tmar-Ben
Ahmed, Beena
description Studies have shown that patients suffering from sleep deprivation have a risk for hypertension, diabetes and depression that is higher than normal sleepers. Treatment for all these problems requires accurate analysis of the sleep stages and patterns in the polysomnographic signals collected in overnight recording over several months. However, manual sleep staging is a repetitive and time-consuming process as marking one typical eight hours overnight polysomnographic recording can take up to two hours to complete. Due to increased processing capabilities, it is now possible to automate this process and assist the sleep expert. A large number of algorithms have been proposed during the last few decades. This review article presents an overview of the existing automatic sleep staging methods, discusses the different challenges and proposes future prospects for new research opportunities.
doi_str_mv 10.1109/IEEEGCC.2013.6705790
format Conference Proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_6705790</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>6705790</ieee_id><sourcerecordid>6705790</sourcerecordid><originalsourceid>FETCH-LOGICAL-c226t-4d1785844be8cf5c4c87c88537de09c3fc0847e57489d155c29f4e7b975d685b3</originalsourceid><addsrcrecordid>eNpVj81Kw0AURkekoNQ8gS7mBRLv_OXOuJMh1kLBjV2XZHInjaRtyCQL317Bblx9nM05fIw9CSiEAPe8rapq430hQaiiRDDo4IZlDq3Q6Byg1Or2H0t3x7KUvgBAIEpr1D1DfzmNy0wTb-pELU8D0cjTXHf9uXvh_lgPA507SjxeJj4ficdlXiZ6YKtYD4my667Z_q369O_57mOz9a-7PEhZzrluBVpjtW7IhmiCDhaD_S1jS-CCigGsRjKorWuFMUG6qAkbh6YtrWnUmj3-eXsiOoxTf6qn78P1rvoBBm5H8Q</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Computer based sleep staging: Challenges for the future</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Hamida, Sana Tmar-Ben ; Ahmed, Beena</creator><creatorcontrib>Hamida, Sana Tmar-Ben ; Ahmed, Beena</creatorcontrib><description>Studies have shown that patients suffering from sleep deprivation have a risk for hypertension, diabetes and depression that is higher than normal sleepers. Treatment for all these problems requires accurate analysis of the sleep stages and patterns in the polysomnographic signals collected in overnight recording over several months. However, manual sleep staging is a repetitive and time-consuming process as marking one typical eight hours overnight polysomnographic recording can take up to two hours to complete. Due to increased processing capabilities, it is now possible to automate this process and assist the sleep expert. A large number of algorithms have been proposed during the last few decades. This review article presents an overview of the existing automatic sleep staging methods, discusses the different challenges and proposes future prospects for new research opportunities.</description><identifier>ISBN: 9781479907229</identifier><identifier>ISBN: 1479907227</identifier><identifier>EISBN: 9781479907243</identifier><identifier>EISBN: 1479907235</identifier><identifier>EISBN: 9781479907236</identifier><identifier>EISBN: 1479907243</identifier><identifier>DOI: 10.1109/IEEEGCC.2013.6705790</identifier><language>eng</language><publisher>IEEE</publisher><subject>Automatic sleep staging ; Biomedical systems ; Classification ; Conferences ; Electroencephalography ; Electromyography ; Electrooculography ; Feature extraction ; Features extraction ; PSG signals ; Sleep ; Sleep deprivation</subject><ispartof>2013 7th IEEE GCC Conference and Exhibition (GCC), 2013, p.280-285</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c226t-4d1785844be8cf5c4c87c88537de09c3fc0847e57489d155c29f4e7b975d685b3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6705790$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2052,27902,54895</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6705790$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Hamida, Sana Tmar-Ben</creatorcontrib><creatorcontrib>Ahmed, Beena</creatorcontrib><title>Computer based sleep staging: Challenges for the future</title><title>2013 7th IEEE GCC Conference and Exhibition (GCC)</title><addtitle>IEEEGCC</addtitle><description>Studies have shown that patients suffering from sleep deprivation have a risk for hypertension, diabetes and depression that is higher than normal sleepers. Treatment for all these problems requires accurate analysis of the sleep stages and patterns in the polysomnographic signals collected in overnight recording over several months. However, manual sleep staging is a repetitive and time-consuming process as marking one typical eight hours overnight polysomnographic recording can take up to two hours to complete. Due to increased processing capabilities, it is now possible to automate this process and assist the sleep expert. A large number of algorithms have been proposed during the last few decades. This review article presents an overview of the existing automatic sleep staging methods, discusses the different challenges and proposes future prospects for new research opportunities.</description><subject>Automatic sleep staging</subject><subject>Biomedical systems</subject><subject>Classification</subject><subject>Conferences</subject><subject>Electroencephalography</subject><subject>Electromyography</subject><subject>Electrooculography</subject><subject>Feature extraction</subject><subject>Features extraction</subject><subject>PSG signals</subject><subject>Sleep</subject><subject>Sleep deprivation</subject><isbn>9781479907229</isbn><isbn>1479907227</isbn><isbn>9781479907243</isbn><isbn>1479907235</isbn><isbn>9781479907236</isbn><isbn>1479907243</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2013</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpVj81Kw0AURkekoNQ8gS7mBRLv_OXOuJMh1kLBjV2XZHInjaRtyCQL317Bblx9nM05fIw9CSiEAPe8rapq430hQaiiRDDo4IZlDq3Q6Byg1Or2H0t3x7KUvgBAIEpr1D1DfzmNy0wTb-pELU8D0cjTXHf9uXvh_lgPA507SjxeJj4ficdlXiZ6YKtYD4my667Z_q369O_57mOz9a-7PEhZzrluBVpjtW7IhmiCDhaD_S1jS-CCigGsRjKorWuFMUG6qAkbh6YtrWnUmj3-eXsiOoxTf6qn78P1rvoBBm5H8Q</recordid><startdate>201311</startdate><enddate>201311</enddate><creator>Hamida, Sana Tmar-Ben</creator><creator>Ahmed, Beena</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201311</creationdate><title>Computer based sleep staging: Challenges for the future</title><author>Hamida, Sana Tmar-Ben ; Ahmed, Beena</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c226t-4d1785844be8cf5c4c87c88537de09c3fc0847e57489d155c29f4e7b975d685b3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Automatic sleep staging</topic><topic>Biomedical systems</topic><topic>Classification</topic><topic>Conferences</topic><topic>Electroencephalography</topic><topic>Electromyography</topic><topic>Electrooculography</topic><topic>Feature extraction</topic><topic>Features extraction</topic><topic>PSG signals</topic><topic>Sleep</topic><topic>Sleep deprivation</topic><toplevel>online_resources</toplevel><creatorcontrib>Hamida, Sana Tmar-Ben</creatorcontrib><creatorcontrib>Ahmed, Beena</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Hamida, Sana Tmar-Ben</au><au>Ahmed, Beena</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Computer based sleep staging: Challenges for the future</atitle><btitle>2013 7th IEEE GCC Conference and Exhibition (GCC)</btitle><stitle>IEEEGCC</stitle><date>2013-11</date><risdate>2013</risdate><spage>280</spage><epage>285</epage><pages>280-285</pages><isbn>9781479907229</isbn><isbn>1479907227</isbn><eisbn>9781479907243</eisbn><eisbn>1479907235</eisbn><eisbn>9781479907236</eisbn><eisbn>1479907243</eisbn><abstract>Studies have shown that patients suffering from sleep deprivation have a risk for hypertension, diabetes and depression that is higher than normal sleepers. Treatment for all these problems requires accurate analysis of the sleep stages and patterns in the polysomnographic signals collected in overnight recording over several months. However, manual sleep staging is a repetitive and time-consuming process as marking one typical eight hours overnight polysomnographic recording can take up to two hours to complete. Due to increased processing capabilities, it is now possible to automate this process and assist the sleep expert. A large number of algorithms have been proposed during the last few decades. This review article presents an overview of the existing automatic sleep staging methods, discusses the different challenges and proposes future prospects for new research opportunities.</abstract><pub>IEEE</pub><doi>10.1109/IEEEGCC.2013.6705790</doi><tpages>6</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISBN: 9781479907229
ispartof 2013 7th IEEE GCC Conference and Exhibition (GCC), 2013, p.280-285
issn
language eng
recordid cdi_ieee_primary_6705790
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Automatic sleep staging
Biomedical systems
Classification
Conferences
Electroencephalography
Electromyography
Electrooculography
Feature extraction
Features extraction
PSG signals
Sleep
Sleep deprivation
title Computer based sleep staging: Challenges for the future
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-13T02%3A49%3A06IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Computer%20based%20sleep%20staging:%20Challenges%20for%20the%20future&rft.btitle=2013%207th%20IEEE%20GCC%20Conference%20and%20Exhibition%20(GCC)&rft.au=Hamida,%20Sana%20Tmar-Ben&rft.date=2013-11&rft.spage=280&rft.epage=285&rft.pages=280-285&rft.isbn=9781479907229&rft.isbn_list=1479907227&rft_id=info:doi/10.1109/IEEEGCC.2013.6705790&rft_dat=%3Cieee_6IE%3E6705790%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&rft.eisbn=9781479907243&rft.eisbn_list=1479907235&rft.eisbn_list=9781479907236&rft.eisbn_list=1479907243&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=6705790&rfr_iscdi=true