{"id":"https://openalex.org/W3082823829","doi":"https://doi.org/10.1109/icaci49185.2020.9177520","title":"An Automatic Sleep Staging Model Combining Feature Learning and Sequence Learning","display_name":"An Automatic Sleep Staging Model Combining Feature Learning and Sequence Learning","publication_year":2020,"publication_date":"2020-08-01","ids":{"openalex":"https://openalex.org/W3082823829","doi":"https://doi.org/10.1109/icaci49185.2020.9177520","mag":"3082823829"},"language":"en","primary_location":{"id":"doi:10.1109/icaci49185.2020.9177520","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaci49185.2020.9177520","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 12th International Conference on Advanced Computational Intelligence (ICACI)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100676451","display_name":"Yinghao Li","orcid":"https://orcid.org/0000-0001-9584-8159"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yinghao Li","raw_affiliation_strings":["School of Automation Science and Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Automation Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048899636","display_name":"Zhenghui Gu","orcid":"https://orcid.org/0000-0001-9365-2953"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenghui Gu","raw_affiliation_strings":["School of Automation Science and Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Automation Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045470727","display_name":"Zichao Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zichao Lin","raw_affiliation_strings":["School of Automation Science and Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Automation Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110615211","display_name":"Zhuliang Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuliang Yu","raw_affiliation_strings":["School of Automation Science and Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Automation Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100672536","display_name":"Yuanqing Li","orcid":"https://orcid.org/0000-0003-4288-5591"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanqing Li","raw_affiliation_strings":["School of Automation Science and Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Automation Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100676451"],"corresponding_institution_ids":["https://openalex.org/I90610280"],"apc_list":null,"apc_paid":null,"fwci":0.4546,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.60648139,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":"2020","issue":null,"first_page":"419","last_page":"425"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10234","display_name":"Obstructive Sleep Apnea Research","score":0.9876000285148621,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11373","display_name":"Sleep and Work-Related Fatigue","score":0.9829000234603882,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.786186933517456},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6838709712028503},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6348349452018738},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5680332183837891},{"id":"https://openalex.org/keywords/sleep-stages","display_name":"Sleep Stages","score":0.5634417533874512},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.521872878074646},{"id":"https://openalex.org/keywords/sleep","display_name":"Sleep (system call)","score":0.5199707746505737},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5172308087348938},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4871344268321991},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45217329263687134},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4310021996498108},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42763781547546387},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.10775849223136902},{"id":"https://openalex.org/keywords/polysomnography","display_name":"Polysomnography","score":0.0777149498462677}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.786186933517456},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6838709712028503},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6348349452018738},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5680332183837891},{"id":"https://openalex.org/C2910364982","wikidata":"https://www.wikidata.org/wiki/Q35831","display_name":"Sleep Stages","level":4,"score":0.5634417533874512},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.521872878074646},{"id":"https://openalex.org/C2775841894","wikidata":"https://www.wikidata.org/wiki/Q4683692","display_name":"Sleep (system call)","level":2,"score":0.5199707746505737},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5172308087348938},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4871344268321991},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45217329263687134},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4310021996498108},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42763781547546387},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.10775849223136902},{"id":"https://openalex.org/C2778205975","wikidata":"https://www.wikidata.org/wiki/Q1754874","display_name":"Polysomnography","level":3,"score":0.0777149498462677},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icaci49185.2020.9177520","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaci49185.2020.9177520","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 12th International Conference on Advanced Computational Intelligence (ICACI)","raw_type":"proceedings-article"},{"id":"mag:3161661569","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002244342339757","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1799366690","https://openalex.org/W1995200202","https://openalex.org/W2064675550","https://openalex.org/W2118978333","https://openalex.org/W2131774270","https://openalex.org/W2133564696","https://openalex.org/W2143159308","https://openalex.org/W2163462953","https://openalex.org/W2164082066","https://openalex.org/W2258794826","https://openalex.org/W2513213398","https://openalex.org/W2529700114","https://openalex.org/W2604096629","https://openalex.org/W2612047884","https://openalex.org/W2760962311","https://openalex.org/W2790486743","https://openalex.org/W2805033630","https://openalex.org/W2893892260","https://openalex.org/W2899090218","https://openalex.org/W2912943321","https://openalex.org/W2921754499","https://openalex.org/W2963446712","https://openalex.org/W2963919481","https://openalex.org/W2964308564","https://openalex.org/W3152633770","https://openalex.org/W3166543270","https://openalex.org/W6638444622","https://openalex.org/W6679434410","https://openalex.org/W6727807574","https://openalex.org/W6744702448","https://openalex.org/W6760028777","https://openalex.org/W6776930347"],"related_works":["https://openalex.org/W3121188996","https://openalex.org/W4308561096","https://openalex.org/W3200508116","https://openalex.org/W2136162213","https://openalex.org/W2376497661","https://openalex.org/W3011076523","https://openalex.org/W2332107599","https://openalex.org/W2319810220","https://openalex.org/W2424678138","https://openalex.org/W2324099496"],"abstract_inverted_index":{"Sleep":[0,124],"stage":[1,25],"classification":[2,26,74,88,121],"is":[3,13,76],"a":[4],"technique":[5],"for":[6],"analyzing":[7],"sleep":[8,11,24],"quality.":[9],"Manual":[10],"staging":[12],"time-consuming":[14],"and":[15,31,41,102,112,128],"laborious.":[16],"In":[17,57],"this":[18],"paper,":[19],"we":[20,59],"propose":[21],"an":[22],"automatic":[23],"model":[27],"combining":[28],"feature":[29],"learning":[30],"sequence":[32,44],"learning,":[33],"which":[34],"extract":[35],"features":[36],"with":[37,54],"convolutional":[38],"neural":[39],"network(CNN)":[40],"learn":[42],"the":[43,65,87,119],"transition":[45,70,91],"rule":[46],"through":[47],"multi-layer":[48],"long":[49],"short":[50],"term":[51],"memory(LSTM)":[52],"architecture":[53],"attention":[55],"mechanism.":[56],"addition,":[58],"also":[60],"noticed":[61],"that":[62],"most":[63],"of":[64,90,110],"misclassified":[66],"samples":[67],"locate":[68],"in":[69],"period.":[71,92],"Therefore,":[72],"multi-label":[73],"scheme":[75],"introduced":[77],"to":[78,85],"provide":[79],"more":[80],"label":[81],"information,":[82],"so":[83],"as":[84],"improve":[86],"performance":[89,122],"We":[93],"evaluate":[94],"on":[95,123,132],"two":[96],"public":[97],"datasets":[98],"(Sleep":[99],"EDF":[100,125],"Expanded":[101,126],"Physionet2018),":[103],"where":[104],"our":[105],"framework":[106],"reaches":[107],"macro":[108],"F1-score":[109],"79.7":[111],"79.8,":[113],"respectively.":[114],"The":[115],"proposed":[116],"network":[117],"achieves":[118],"state-of-the-art":[120],"dataset":[127],"sets":[129],"new":[130],"benchmark":[131],"Physionet2018":[133],"dataset.":[134]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
