{"id":"https://openalex.org/W4360605036","doi":"https://doi.org/10.1109/icaiic57133.2023.10066965","title":"An End-to-End Convolutional Recurrent Neural Network with Multi-Source Data Fusion for Sleep Stage Classification","display_name":"An End-to-End Convolutional Recurrent Neural Network with Multi-Source Data Fusion for Sleep Stage Classification","publication_year":2023,"publication_date":"2023-02-20","ids":{"openalex":"https://openalex.org/W4360605036","doi":"https://doi.org/10.1109/icaiic57133.2023.10066965"},"language":"en","primary_location":{"id":"doi:10.1109/icaiic57133.2023.10066965","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaiic57133.2023.10066965","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","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/A5046488404","display_name":"Tabassum Islam Toma","orcid":"https://orcid.org/0000-0003-4447-9562"},"institutions":[{"id":"https://openalex.org/I110273157","display_name":"Kookmin University","ror":"https://ror.org/0049erg63","country_code":"KR","type":"education","lineage":["https://openalex.org/I110273157"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Tabassum Islam Toma","raw_affiliation_strings":["Kookmin University,Department of Electronics Engineering,Seoul,Korea,02707"],"affiliations":[{"raw_affiliation_string":"Kookmin University,Department of Electronics Engineering,Seoul,Korea,02707","institution_ids":["https://openalex.org/I110273157"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068241503","display_name":"Sunwoong Choi","orcid":"https://orcid.org/0000-0002-8719-8181"},"institutions":[{"id":"https://openalex.org/I110273157","display_name":"Kookmin University","ror":"https://ror.org/0049erg63","country_code":"KR","type":"education","lineage":["https://openalex.org/I110273157"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sunwoong Choi","raw_affiliation_strings":["Kookmin University,Department of Electronics Engineering,Seoul,Korea,02707"],"affiliations":[{"raw_affiliation_string":"Kookmin University,Department of Electronics Engineering,Seoul,Korea,02707","institution_ids":["https://openalex.org/I110273157"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5046488404"],"corresponding_institution_ids":["https://openalex.org/I110273157"],"apc_list":null,"apc_paid":null,"fwci":1.2673,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.77667068,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"564","last_page":"569"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":1.0,"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":1.0,"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T11021","display_name":"ECG Monitoring and Analysis","score":0.987500011920929,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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":0.7958238124847412},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.769121527671814},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.606706440448761},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5755493640899658},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.572662353515625},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5520303249359131},{"id":"https://openalex.org/keywords/sleep","display_name":"Sleep (system call)","score":0.5064159631729126},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4328887462615967},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4254502058029175},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.42147091031074524},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36803698539733887},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2965056300163269}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7958238124847412},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.769121527671814},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.606706440448761},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5755493640899658},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.572662353515625},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5520303249359131},{"id":"https://openalex.org/C2775841894","wikidata":"https://www.wikidata.org/wiki/Q4683692","display_name":"Sleep (system call)","level":2,"score":0.5064159631729126},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4328887462615967},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4254502058029175},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.42147091031074524},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36803698539733887},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2965056300163269},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icaiic57133.2023.10066965","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaiic57133.2023.10066965","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1820534876","https://openalex.org/W1936750108","https://openalex.org/W2588327383","https://openalex.org/W2604096629","https://openalex.org/W2611695796","https://openalex.org/W2790486743","https://openalex.org/W2792420355","https://openalex.org/W2805033630","https://openalex.org/W2908578648","https://openalex.org/W2908603469","https://openalex.org/W2941679862","https://openalex.org/W2955564905","https://openalex.org/W2963919481","https://openalex.org/W2968779794","https://openalex.org/W3013280810","https://openalex.org/W3023886245","https://openalex.org/W3091714893","https://openalex.org/W4280498896","https://openalex.org/W4297505052"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2745001401","https://openalex.org/W4321353415","https://openalex.org/W2130974462","https://openalex.org/W972276598","https://openalex.org/W4246352526","https://openalex.org/W2028665553","https://openalex.org/W4230315250","https://openalex.org/W4225394202","https://openalex.org/W4298287631"],"abstract_inverted_index":{"Automatic":[0],"sleep":[1,54,78,105,134,282,295],"stage":[2,79,135],"monitoring":[3],"is":[4,148,193,273],"an":[5,112,162,291],"essential":[6],"tool":[7],"for":[8,76],"the":[9,64,77,93,104,141,152,156,227,239,277],"diagnosis":[10],"and":[11,35,42,154,180,198,206,225,248,265],"treatment":[12],"of":[13,52,66,95,176,214,246,253,281],"sleep-related":[14],"disorders":[15],"effectively.":[16],"Although":[17],"extensive":[18],"studies":[19,278],"focusing":[20],"on":[21,70,279],"single":[22,29],"source":[23],"data":[24,114,175],"or":[25,72],"information,":[26],"such":[27],"as":[28,209,284,286,290],"channel":[30,204],"electroencephalogram":[31],"(EEG),":[32],"electrooculogram":[33],"(EOG),":[34],"electromyogram":[36],"(EMG),":[37],"with":[38,211,233,242],"machine":[39],"learning":[40,44],"(ML)":[41],"deep":[43],"(DL)":[45],"have":[46,62,200],"been":[47],"presented":[48],"in":[49,102,129,137,195,217,221,276],"this":[50,138,196],"field":[51],"automatic":[53,133],"staging,":[55],"there":[56],"are":[57],"very":[58,274],"limited":[59],"literature's":[60],"that":[61],"investigated":[63],"impact":[65],"multisource":[67],"information":[68,91],"fusion":[69],"ML":[71],"DL":[73],"based":[74,270],"schemes":[75],"classification.":[80],"In":[81,140],"addition,":[82],"exploiting":[83],"recurrent":[84,125,263],"neural":[85,126],"network":[86,127],"(RNN)":[87],"to":[88,110,131,150,184,223,293],"learn":[89,185],"temporal":[90],"from":[92,173],"sequences":[94],"multi-source":[96,113],"inputs":[97],"can":[98,159,169,181,237,287],"bring":[99],"significant":[100],"improvement":[101],"classifying":[103],"stage.":[106],"Therefore,":[107],"we":[108,199],"aim":[109],"develop":[111],"fusion,":[115,121],"more":[116],"specifically":[117],"two":[118,177,257],"source's":[119],"signal":[120,205,208],"enabled":[122],"end-to-end":[123,163],"convolutional":[124],"(CRNN)":[128],"order":[130,222],"perform":[132],"classification":[136,280],"article.":[139],"proposed":[142,157,166,230],"scheme,":[143],"no":[144],"hand":[145],"crafted":[146],"features":[147,172],"used":[149,194],"train":[151],"model":[153,158,168,218,232],"hence":[155],"be":[160,288],"called":[161],"approach.":[164],"The":[165,229],"CRNN":[167,231],"extract":[170],"time-invariant":[171],"raw":[174],"input":[178,210],"sources":[179],"fuse":[182],"them":[183],"temporally":[186],"correlated":[187],"features.":[188],"Sleep-EDF":[189,240],"expanded":[190],"benchmark":[191],"dataset":[192,241],"study":[197],"employed":[201],"Fpz-Cz":[202],"EEG":[203],"EOG":[207],"3":[212],"variants":[213],"RNN":[215,235,258],"layer":[216,260],"architecture":[219],"separately":[220],"evaluate":[224],"investigate":[226],"performance.":[228],"standard":[234],"layers":[236],"classify":[238],"maximum":[243,249],"average":[244],"accuracy":[245],"90.30%":[247],"Cohen's":[250],"kappa":[251],"coefficient":[252],"86.86":[254],"compared":[255],"other":[256],"variant's":[259],"(e.g.,":[261],"gated":[262],"unit":[264],"long":[266],"short":[267],"term":[268],"memory)":[269],"models":[271],"which":[272],"promising":[275],"stages":[283],"well":[285],"regarded":[289],"alternative":[292],"conventional":[294],"staging.":[296]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
