{"id":"https://openalex.org/W4312503035","doi":"https://doi.org/10.1109/lsp.2022.3215086","title":"DSSNet: A Deep Sequential Sleep Network for Self-Supervised Representation Learning Based on Single-Channel EEG","display_name":"DSSNet: A Deep Sequential Sleep Network for Self-Supervised Representation Learning Based on Single-Channel EEG","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312503035","doi":"https://doi.org/10.1109/lsp.2022.3215086"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2022.3215086","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2022.3215086","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-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/A5072589092","display_name":"Shuohua Chang","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuohua Chang","raw_affiliation_strings":["School of Automation, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-6753-3931","affiliations":[{"raw_affiliation_string":"School of Automation, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069692584","display_name":"Zhihong Yang","orcid":"https://orcid.org/0000-0003-4286-6665"},"institutions":[{"id":"https://openalex.org/I200296433","display_name":"Chinese Academy of Medical Sciences & Peking Union Medical College","ror":"https://ror.org/02drdmm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I200296433"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihong Yang","raw_affiliation_strings":["Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4286-6665","affiliations":[{"raw_affiliation_string":"Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China","institution_ids":["https://openalex.org/I200296433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060298169","display_name":"Yuyang You","orcid":"https://orcid.org/0000-0002-3062-379X"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuyang You","raw_affiliation_strings":["School of Automation, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3062-379X","affiliations":[{"raw_affiliation_string":"School of Automation, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079612504","display_name":"Xiaoyu Guo","orcid":"https://orcid.org/0000-0002-9995-8213"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyu Guo","raw_affiliation_strings":["School of Automation, Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.0627,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.87353504,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"29","issue":null,"first_page":"2143","last_page":"2147"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9991999864578247,"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":0.9991999864578247,"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9884999990463257,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10985","display_name":"Sleep and Wakefulness Research","score":0.9812999963760376,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8061407804489136},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6881848573684692},{"id":"https://openalex.org/keywords/sleep","display_name":"Sleep (system call)","score":0.6581581234931946},{"id":"https://openalex.org/keywords/sleep-stages","display_name":"Sleep Stages","score":0.5719804763793945},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5462604761123657},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5359395742416382},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5012547969818115},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.4998209476470947},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4709794521331787},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4482302665710449},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.35166868567466736},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.33558282256126404},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32209980487823486},{"id":"https://openalex.org/keywords/polysomnography","display_name":"Polysomnography","score":0.15667271614074707},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.09386777877807617}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8061407804489136},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6881848573684692},{"id":"https://openalex.org/C2775841894","wikidata":"https://www.wikidata.org/wiki/Q4683692","display_name":"Sleep (system call)","level":2,"score":0.6581581234931946},{"id":"https://openalex.org/C2910364982","wikidata":"https://www.wikidata.org/wiki/Q35831","display_name":"Sleep Stages","level":4,"score":0.5719804763793945},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5462604761123657},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5359395742416382},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5012547969818115},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.4998209476470947},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4709794521331787},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4482302665710449},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.35166868567466736},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.33558282256126404},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32209980487823486},{"id":"https://openalex.org/C2778205975","wikidata":"https://www.wikidata.org/wiki/Q1754874","display_name":"Polysomnography","level":3,"score":0.15667271614074707},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.09386777877807617},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2022.3215086","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2022.3215086","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2067848998","display_name":null,"funder_award_id":"81273654","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3814635228","display_name":null,"funder_award_id":"7173267","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"},{"id":"https://openalex.org/G4393545708","display_name":null,"funder_award_id":"81473579","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G914215898","display_name":null,"funder_award_id":"81973744","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W2144691514","https://openalex.org/W2152790380","https://openalex.org/W2172894528","https://openalex.org/W2513213398","https://openalex.org/W2604096629","https://openalex.org/W2798991696","https://openalex.org/W2893892260","https://openalex.org/W2944828972","https://openalex.org/W2979579363","https://openalex.org/W3009561768","https://openalex.org/W3034390803","https://openalex.org/W3034781633","https://openalex.org/W3035524453","https://openalex.org/W3043229062","https://openalex.org/W3082394918","https://openalex.org/W3098250197","https://openalex.org/W3101658985","https://openalex.org/W3109466111","https://openalex.org/W3158818505","https://openalex.org/W3161980230","https://openalex.org/W3184196062","https://openalex.org/W3217299532","https://openalex.org/W4220988906","https://openalex.org/W4286695273","https://openalex.org/W4297808394","https://openalex.org/W4312891522","https://openalex.org/W6682948231","https://openalex.org/W6774314701","https://openalex.org/W6774670964","https://openalex.org/W6795754764","https://openalex.org/W6844194202"],"related_works":["https://openalex.org/W4380075502","https://openalex.org/W4223943233","https://openalex.org/W4312200629","https://openalex.org/W4360585206","https://openalex.org/W4364306694","https://openalex.org/W4380086463","https://openalex.org/W4225161397","https://openalex.org/W4220686584","https://openalex.org/W4246751904","https://openalex.org/W3192794374"],"abstract_inverted_index":{"Sleep":[0],"staging":[1,11,60],"by":[2],"highly":[3],"trained":[4],"specialists":[5],"is":[6,55,131],"laborious.":[7],"Although":[8],"automatic":[9],"sleep":[10,59,81],"with":[12,42,67],"supervised":[13],"learning":[14,31],"methods":[15,32,61],"has":[16],"been":[17,35],"implemented":[18],"for":[19,133],"almost":[20],"a":[21,78,84,99],"decade,":[22],"it":[23],"requires":[24],"lots":[25],"of":[26,49,111,120,128,146],"manually":[27],"annotated":[28],"data.":[29],"Self-supervised":[30],"have":[33],"recently":[34],"gaining":[36],"attention.":[37],"They":[38],"can":[39],"learn":[40],"representations":[41,92],"unlabeled":[43],"data,":[44],"which":[45],"alleviates":[46],"the":[47,53,109,121,126],"cost":[48],"labeling":[50],"work.":[51],"However,":[52],"problem":[54],"that":[56,87,125],"these":[57],"self-supervised":[58,85],"either":[62],"require":[63],"prior":[64],"knowledge,":[65],"as":[66],"frequency":[68],"information,":[69],"or":[70],"they":[71],"produce":[72],"unsatisfactory":[73],"results.":[74],"Thus,":[75],"we":[76],"propose":[77],"deep":[79],"sequential":[80],"network":[82],"(DSSNet),":[83],"framework":[86],"aims":[88],"to":[89],"perform":[90],"multi-view":[91],"based":[93],"on":[94,115,139],"contrastive":[95,113],"learning.":[96],"It":[97],"utilizes":[98],"single-channel":[100],"electroencephalogram":[101],"but":[102],"achieves":[103],"competitive":[104],"performance.":[105,117,135],"We":[106,136],"also":[107],"explore":[108],"impact":[110],"different":[112],"mechanisms":[114],"DSSNet":[116,138],"The":[118],"results":[119],"Sleep-EDF":[122,140],"dataset":[123],"prove":[124],"consistency":[127],"negative":[129],"samples":[130],"crucial":[132],"improving":[134],"evaluate":[137],"and":[141,143,148],"ISRUC-Sleep":[142],"achieve":[144],"accuracies":[145],"80.0%":[147],"71.4%.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}