{"id":"https://openalex.org/W2979898276","doi":"https://doi.org/10.1109/embc.2019.8857356","title":"Scalable automatic sleep staging in the era of Big Data","display_name":"Scalable automatic sleep staging in the era of Big Data","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2979898276","doi":"https://doi.org/10.1109/embc.2019.8857356","mag":"2979898276","pmid":"https://pubmed.ncbi.nlm.nih.gov/31946351"},"language":"en","primary_location":{"id":"doi:10.1109/embc.2019.8857356","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2019.8857356","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5016678006","display_name":"Takashi Nakamura","orcid":"https://orcid.org/0000-0002-7354-2279"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Takashi Nakamura","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Imperial College, London, UK"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Imperial College, London, UK","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033945689","display_name":"Harry J. Davies","orcid":"https://orcid.org/0000-0001-7506-2300"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Harry J. Davies","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Imperial College, London, UK"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Imperial College, London, UK","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103001848","display_name":"Danilo P. Mandic","orcid":"https://orcid.org/0000-0001-8432-3963"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Danilo P. Mandic","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Imperial College, London, UK"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Imperial College, London, UK","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5016678006"],"corresponding_institution_ids":["https://openalex.org/I47508984"],"apc_list":null,"apc_paid":null,"fwci":0.6081,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.66782302,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"2019","issue":null,"first_page":"2265","last_page":"2268"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9983999729156494,"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":0.9983999729156494,"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/T12676","display_name":"Machine Learning and ELM","score":0.993399977684021,"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/T11184","display_name":"Neonatal and fetal brain pathology","score":0.9868000149726868,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7579219341278076},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5591210126876831},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5235285758972168},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.5177227854728699},{"id":"https://openalex.org/keywords/polysomnography","display_name":"Polysomnography","score":0.48177000880241394},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4604279696941376},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.43486976623535156},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.43082189559936523},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3841671049594879},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.14929819107055664}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7579219341278076},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5591210126876831},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5235285758972168},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.5177227854728699},{"id":"https://openalex.org/C2778205975","wikidata":"https://www.wikidata.org/wiki/Q1754874","display_name":"Polysomnography","level":3,"score":0.48177000880241394},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4604279696941376},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.43486976623535156},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.43082189559936523},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3841671049594879},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.14929819107055664},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","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/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C2781326671","wikidata":"https://www.wikidata.org/wiki/Q754424","display_name":"Apnea","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[{"descriptor_ui":"D000077558","descriptor_name":"Big Data","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077558","descriptor_name":"Big Data","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077558","descriptor_name":"Big Data","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004569","descriptor_name":"Electroencephalography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004569","descriptor_name":"Electroencephalography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004569","descriptor_name":"Electroencephalography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012815","descriptor_name":"Signal Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012815","descriptor_name":"Signal Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012815","descriptor_name":"Signal Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012894","descriptor_name":"Sleep Stages","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012894","descriptor_name":"Sleep Stages","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012894","descriptor_name":"Sleep Stages","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1109/embc.2019.8857356","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2019.8857356","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","raw_type":"proceedings-article"},{"id":"pmid:31946351","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31946351","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":null},{"id":"pmh:oai:spiral.imperial.ac.uk:10044/1/69974","is_oa":false,"landing_page_url":"http://hdl.handle.net/10044/1/69974","pdf_url":null,"source":{"id":"https://openalex.org/S4306401396","display_name":"Spiral (Imperial College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I47508984","host_organization_name":"Imperial College London","host_organization_lineage":["https://openalex.org/I47508984"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE EMBC 2019","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4399999976158142,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[{"id":"https://openalex.org/G8717732828","display_name":null,"funder_award_id":"2124521","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1983256092","https://openalex.org/W2058807024","https://openalex.org/W2111072639","https://openalex.org/W2155264706","https://openalex.org/W2162800060","https://openalex.org/W2344257056","https://openalex.org/W2626881725","https://openalex.org/W2771338643","https://openalex.org/W2792489592","https://openalex.org/W2884525847","https://openalex.org/W6683151225"],"related_works":["https://openalex.org/W3085383590","https://openalex.org/W2961085424","https://openalex.org/W2106383973","https://openalex.org/W2013930426","https://openalex.org/W4306674287","https://openalex.org/W2354062721","https://openalex.org/W4224009465","https://openalex.org/W2389896045","https://openalex.org/W3202637261","https://openalex.org/W2137623312"],"abstract_inverted_index":{"Numerous":[0],"automatic":[1,46,94,202],"sleep":[2,47,95,169,203],"staging":[3,48,96],"approaches":[4],"have":[5],"been":[6],"proposed":[7],"to":[8,13,88,104,142,175],"provide":[9],"an":[10,146],"eHealth":[11],"alternative":[12],"the":[14,37,40,56,63,91,105,156,164,167,181],"current":[15],"gold-standard":[16],"-":[17],"hypnogram":[18],"scoring":[19],"by":[20,145],"human":[21],"experts.":[22],"However,":[23],"a":[24,72,84,119,205],"majority":[25],"of":[26,31,44,62,93,107,122,163,187,207],"such":[27,45],"studies":[28],"exploit":[29],"data":[30],"limited":[32],"scale,":[33],"which":[34,152],"compromises":[35],"both":[36,177,219],"validation":[38],"and":[39,42,59,112,137,180,200,212,222],"reproducibility":[41],"transferability":[43],"systems":[49],"in":[50,75,153],"real":[51],"clinical":[52],"settings.":[53],"In":[54],"addition,":[55],"computational":[57],"issues":[58],"physical":[60],"meaningfulness":[61],"analysis":[64,86],"are":[65],"typically":[66],"neglected,":[67],"yet":[68],"affordable":[69,135,221],"computation":[70,136,179],"is":[71,116,140,173,195,218],"key":[73],"criterion":[74],"Big":[76],"Data":[77],"analytics.":[78],"To":[79],"this":[80],"end,":[81],"we":[82],"establish":[83],"comprehensive":[85],"framework":[87],"rigorously":[89],"evaluate":[90],"feasibility":[92],"from":[97],"multiple":[98],"perspectives,":[99],"including":[100],"robustness":[101],"with":[102,155],"respect":[103],"number":[106],"training":[108],"subjects,":[109],"model":[110,161],"complexity,":[111],"different":[113,168],"classifiers.":[114],"This":[115],"achieved":[117],"for":[118,198],"large":[120],"collection":[121],"publicly":[123],"accessible":[124],"polysomnography":[125],"(PSG)":[126],"data,":[127],"recorded":[128],"over":[129],"515":[130],"subjects.":[131],"The":[132],"trade-off":[133],"between":[134,166],"satisfactory":[138],"accuracy":[139],"shown":[141,174,196],"be":[143],"fulfilled":[144],"extreme":[147],"learning":[148],"machine":[149],"(ELM)":[150],"classifier,":[151],"conjunction":[154],"physically":[157,223],"meaningful":[158],"hidden":[159],"Markov":[160],"(HMM)":[162],"transition":[165],"stages":[170],"(smoothing":[171],"model)":[172],"achieve":[176],"fast":[178],"highest":[182],"average":[183],"Cohen's":[184],"kappa":[185],"value":[186],"\u03ba":[188],"=":[189],"0.73":[190],"(Substantial":[191],"Agreement).":[192],"Finally,":[193],"it":[194],"that":[197],"accurate":[199],"robust":[201],"staging,":[204],"combination":[206],"structural":[208],"complexity":[209],"(multi-scale":[210],"entropy)":[211],"frequency-domain":[213],"(spectral":[214],"edge":[215],"frequency)":[216],"features":[217],"computationally":[220],"meaningful.":[224]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
