Automatic Sleep Stage Scoring Using Hilbert-Huang Transform with BP Neural Network
In this paper, a novel method based on Hilbert-Huang Transform (HHT) and backpropagation (BP) neural network is proposed to perform automatic sleep stages classification. Features extracted from 30-second epoch of EEG using HHT are good representations of EEG signal. A three-layer BP neural network...
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| creator | Yuelei Liu Lanfeng Yan Bo Zeng Wei Wang |
| description | In this paper, a novel method based on Hilbert-Huang Transform (HHT) and backpropagation (BP) neural network is proposed to perform automatic sleep stages classification. Features extracted from 30-second epoch of EEG using HHT are good representations of EEG signal. A three-layer BP neural network is employed to classify these features to one appropriate stage. For a four-stage classification, consisting of Awake, Stage 1 + REM, Stage 2 and slow wave stage (SWS), of one single Pz-Oz channel EEG signal alone from 7 human subjects, the average stage recognition rate of the proposed method can achieve Awake 95.2%, Stage 1+Rem 87.1%, Stage 2 82.0%, SWS 92.9%. The experiment results show the method is effective and promising in automatic sleep states classification. It can be a powerful tool in sleep quality monitoring and sleep-related diseases diagnosis. |
| doi_str_mv | 10.1109/ICBBE.2010.5516372 |
| format | Conference Proceeding |
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It can be a powerful tool in sleep quality monitoring and sleep-related diseases diagnosis.</description><subject>Data mining</subject><subject>Diseases</subject><subject>Electroencephalography</subject><subject>Feature extraction</subject><subject>Hospitals</subject><subject>Information science</subject><subject>Low voltage</subject><subject>Neural networks</subject><subject>Sleep</subject><subject>Time frequency analysis</subject><issn>2151-7614</issn><issn>2151-7622</issn><isbn>9781424447121</isbn><isbn>1424447127</isbn><isbn>9781424447138</isbn><isbn>1424447135</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpVkM1OAjEUhesPiYi8gG76AoO97XTaLoGgkBA1AmvSmbnF6sCQTgnh7R0jMXFzTr6c5FscQu6BDQCYeZyNR6PJgLOWpYRMKH5B-kZpSHmapgqEviRdDhISlXF-9W_jcP23Qdoht5wxY5gEnd2QftN8MtZ6lTFGdcn78BDrrY2-oIsKcU8X0W6QLoo6-N2GrpqfnPoqxxCT6cG2tAx217g6bOnRxw86eqMveAi2aise6_B1RzrOVg32z90jq6fJcjxN5q_Ps_FwnnhQMiZgZKa1FblDLnPkuXDOIOYuL8Hy0rrCSm3QKYmFzjKmFDelkabUAhUyFD3y8Ov1iLjeB7-14bQ-3yW-ATFSWCk</recordid><startdate>201006</startdate><enddate>201006</enddate><creator>Yuelei Liu</creator><creator>Lanfeng Yan</creator><creator>Bo Zeng</creator><creator>Wei Wang</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201006</creationdate><title>Automatic Sleep Stage Scoring Using Hilbert-Huang Transform with BP Neural Network</title><author>Yuelei Liu ; Lanfeng Yan ; Bo Zeng ; Wei Wang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-195688a3bfe25be2b3ff9eebfbd1a2dafca589ef75ec86607729d959d83e7e0e3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Data mining</topic><topic>Diseases</topic><topic>Electroencephalography</topic><topic>Feature extraction</topic><topic>Hospitals</topic><topic>Information science</topic><topic>Low voltage</topic><topic>Neural networks</topic><topic>Sleep</topic><topic>Time frequency analysis</topic><toplevel>online_resources</toplevel><creatorcontrib>Yuelei Liu</creatorcontrib><creatorcontrib>Lanfeng Yan</creatorcontrib><creatorcontrib>Bo Zeng</creatorcontrib><creatorcontrib>Wei Wang</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>Yuelei Liu</au><au>Lanfeng Yan</au><au>Bo Zeng</au><au>Wei Wang</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Automatic Sleep Stage Scoring Using Hilbert-Huang Transform with BP Neural Network</atitle><btitle>2010 4th International Conference on Bioinformatics and Biomedical Engineering</btitle><stitle>ICBBE</stitle><date>2010-06</date><risdate>2010</risdate><spage>1</spage><epage>4</epage><pages>1-4</pages><issn>2151-7614</issn><eissn>2151-7622</eissn><isbn>9781424447121</isbn><isbn>1424447127</isbn><eisbn>9781424447138</eisbn><eisbn>1424447135</eisbn><abstract>In this paper, a novel method based on Hilbert-Huang Transform (HHT) and backpropagation (BP) neural network is proposed to perform automatic sleep stages classification. Features extracted from 30-second epoch of EEG using HHT are good representations of EEG signal. A three-layer BP neural network is employed to classify these features to one appropriate stage. For a four-stage classification, consisting of Awake, Stage 1 + REM, Stage 2 and slow wave stage (SWS), of one single Pz-Oz channel EEG signal alone from 7 human subjects, the average stage recognition rate of the proposed method can achieve Awake 95.2%, Stage 1+Rem 87.1%, Stage 2 82.0%, SWS 92.9%. The experiment results show the method is effective and promising in automatic sleep states classification. It can be a powerful tool in sleep quality monitoring and sleep-related diseases diagnosis.</abstract><pub>IEEE</pub><doi>10.1109/ICBBE.2010.5516372</doi><tpages>4</tpages></addata></record> |
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| identifier | ISSN: 2151-7614 |
| ispartof | 2010 4th International Conference on Bioinformatics and Biomedical Engineering, 2010, p.1-4 |
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| language | eng |
| recordid | cdi_ieee_primary_5516372 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Data mining Diseases Electroencephalography Feature extraction Hospitals Information science Low voltage Neural networks Sleep Time frequency analysis |
| title | Automatic Sleep Stage Scoring Using Hilbert-Huang Transform with BP Neural Network |
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