Dual approach for automated sleep spindles detection within EEG background activity in infant polysomnograms
An automated system for sleep spindles detection within EEG background activity, combining two different approaches, is presented. The first approach applies detection criteria on the sigma-band filtered EEG signal, including fuzzy thresholds. The second approach mimics an expert's procedure. A...
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creator | Held, C.M. Causa, L. Estevez, P. Perez, C. Garrido, M. Algarin, C. Peirano, P. |
description | An automated system for sleep spindles detection within EEG background activity, combining two different approaches, is presented. The first approach applies detection criteria on the sigma-band filtered EEG signal, including fuzzy thresholds. The second approach mimics an expert's procedure. A sleep spindle detection is validated if both approaches agree. The method was applied on a testing set, consisting of continuous sleep recordings of two patients, totaling 1132 epochs (pages). A total of 803 sleep spindles events were marked by the experts. Results showed an 87.7% agreement between the detection system and the medical experts. |
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Results showed an 87.7% agreement between the detection system and the medical experts.</description><subject>EEG</subject><subject>Electroencephalography</subject><subject>Electromyography</subject><subject>Electrooculography</subject><subject>Humans</subject><subject>infants sleep</subject><subject>Pathology</subject><subject>Pattern recognition</subject><subject>Pediatrics</subject><subject>Sleep</subject><subject>sleep spindles</subject><subject>Support vector machine classification</subject><subject>Support vector machines</subject><isbn>0780384393</isbn><isbn>9780780384392</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2004</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNp9zrFuwjAUBVBLqFKh5Qfa5f0A4SWO1GRtCYWBqd3Ra_KSuHVsy3ZA-ftmYOYuV1dnuUK8pJikKZbbY3V6_0oyxDxJc5RZhguxwrcCZZHLUj6KdQi_OEeW8y6WQu9G0kDOeUt1D631QGO0A0VuIGhmB8Ep02gO0HDkOipr4KpirwxU1Sf8UP3XeTuaBmjGi4oTzKRMSyaCs3oKdjC28zSEZ_HQkg68vvWTeN1X3x-HjWLms_NqID-db8flff0HmVZKGg</recordid><startdate>2004</startdate><enddate>2004</enddate><creator>Held, C.M.</creator><creator>Causa, L.</creator><creator>Estevez, P.</creator><creator>Perez, C.</creator><creator>Garrido, M.</creator><creator>Algarin, C.</creator><creator>Peirano, P.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>2004</creationdate><title>Dual approach for automated sleep spindles detection within EEG background activity in infant polysomnograms</title><author>Held, C.M. ; Causa, L. ; Estevez, P. ; Perez, C. ; Garrido, M. ; Algarin, C. ; Peirano, P.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-ieee_primary_14032203</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2004</creationdate><topic>EEG</topic><topic>Electroencephalography</topic><topic>Electromyography</topic><topic>Electrooculography</topic><topic>Humans</topic><topic>infants sleep</topic><topic>Pathology</topic><topic>Pattern recognition</topic><topic>Pediatrics</topic><topic>Sleep</topic><topic>sleep spindles</topic><topic>Support vector machine classification</topic><topic>Support vector machines</topic><toplevel>online_resources</toplevel><creatorcontrib>Held, C.M.</creatorcontrib><creatorcontrib>Causa, L.</creatorcontrib><creatorcontrib>Estevez, P.</creatorcontrib><creatorcontrib>Perez, C.</creatorcontrib><creatorcontrib>Garrido, M.</creatorcontrib><creatorcontrib>Algarin, C.</creatorcontrib><creatorcontrib>Peirano, P.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Held, C.M.</au><au>Causa, L.</au><au>Estevez, P.</au><au>Perez, C.</au><au>Garrido, M.</au><au>Algarin, C.</au><au>Peirano, P.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Dual approach for automated sleep spindles detection within EEG background activity in infant polysomnograms</atitle><btitle>The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society</btitle><stitle>IEMBS</stitle><date>2004</date><risdate>2004</risdate><volume>1</volume><spage>566</spage><epage>569</epage><pages>566-569</pages><isbn>0780384393</isbn><isbn>9780780384392</isbn><abstract>An automated system for sleep spindles detection within EEG background activity, combining two different approaches, is presented. The first approach applies detection criteria on the sigma-band filtered EEG signal, including fuzzy thresholds. The second approach mimics an expert's procedure. A sleep spindle detection is validated if both approaches agree. The method was applied on a testing set, consisting of continuous sleep recordings of two patients, totaling 1132 epochs (pages). A total of 803 sleep spindles events were marked by the experts. Results showed an 87.7% agreement between the detection system and the medical experts.</abstract><pub>IEEE</pub><doi>10.1109/IEMBS.2004.1403220</doi></addata></record> |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | EEG Electroencephalography Electromyography Electrooculography Humans infants sleep Pathology Pattern recognition Pediatrics Sleep sleep spindles Support vector machine classification Support vector machines |
title | Dual approach for automated sleep spindles detection within EEG background activity in infant polysomnograms |
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