{"id":"https://openalex.org/W3205480987","doi":"https://doi.org/10.3390/e23101316","title":"Deep Coupling Recurrent Auto-Encoder with Multi-Modal EEG and EOG for Vigilance Estimation","display_name":"Deep Coupling Recurrent Auto-Encoder with Multi-Modal EEG and EOG for Vigilance Estimation","publication_year":2021,"publication_date":"2021-10-09","ids":{"openalex":"https://openalex.org/W3205480987","doi":"https://doi.org/10.3390/e23101316","mag":"3205480987","pmid":"https://pubmed.ncbi.nlm.nih.gov/34682040"},"language":"en","primary_location":{"id":"doi:10.3390/e23101316","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e23101316","pdf_url":"https://www.mdpi.com/1099-4300/23/10/1316/pdf?version=1634536082","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/23/10/1316/pdf?version=1634536082","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072963091","display_name":"Kuiyong Song","orcid":null},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]},{"id":"https://openalex.org/I4210135888","display_name":"Hulunbuir University","ror":"https://ror.org/02vx41k98","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210135888"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kuiyong Song","raw_affiliation_strings":["College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China","Department of Information Engineering, Hulunbuir Vocational Technical College, Hulunbuir 021000, China"],"raw_orcid":"https://orcid.org/0000-0003-4550-3173","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China","institution_ids":["https://openalex.org/I151727225"]},{"raw_affiliation_string":"Department of Information Engineering, Hulunbuir Vocational Technical College, Hulunbuir 021000, China","institution_ids":["https://openalex.org/I4210135888"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021313030","display_name":"Lianke Zhou","orcid":"https://orcid.org/0000-0002-3601-9286"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianke Zhou","raw_affiliation_strings":["College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101784253","display_name":"Hongbin Wang","orcid":"https://orcid.org/0000-0002-5925-4924"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hongbin Wang","raw_affiliation_strings":["College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China","institution_ids":["https://openalex.org/I151727225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101784253"],"corresponding_institution_ids":["https://openalex.org/I151727225"],"apc_list":{"value":2600,"currency":"CHF","value_usd":3137},"apc_paid":{"value":2600,"currency":"CHF","value_usd":3137},"fwci":2.3581,"has_fulltext":true,"cited_by_count":19,"citation_normalized_percentile":{"value":0.8837075,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"23","issue":"10","first_page":"1316","last_page":"1316"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11373","display_name":"Sleep and Work-Related Fatigue","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T11373","display_name":"Sleep and Work-Related Fatigue","score":0.9997000098228455,"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"}},{"id":"https://openalex.org/T10525","display_name":"Human-Automation Interaction and Safety","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6343011260032654},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5264759063720703},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.5089569091796875},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.503680408000946},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4785897731781006},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.461395263671875},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.42180532217025757},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35568946599960327},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22583669424057007},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15760070085525513}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6343011260032654},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5264759063720703},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.5089569091796875},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.503680408000946},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4785897731781006},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.461395263671875},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.42180532217025757},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35568946599960327},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22583669424057007},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15760070085525513},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/e23101316","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e23101316","pdf_url":"https://www.mdpi.com/1099-4300/23/10/1316/pdf?version=1634536082","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:34682040","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34682040","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":"Entropy (Basel, Switzerland)","raw_type":"Journal Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:8534880","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8534880","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:690264882e1e42029a3fdbbce99348e0","is_oa":true,"landing_page_url":"https://doaj.org/article/690264882e1e42029a3fdbbce99348e0","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 23, Iss 10, p 1316 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1099-4300/23/10/1316/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/e23101316","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy; Volume 23; Issue 10; Pages: 1316","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e23101316","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e23101316","pdf_url":"https://www.mdpi.com/1099-4300/23/10/1316/pdf?version=1634536082","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5706948923","display_name":"\u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7684\u6c34\u4e0b\u590d\u6742\u73af\u5883\u611f\u77e5\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"61772152","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"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3205480987.pdf","grobid_xml":"https://content.openalex.org/works/W3205480987.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W158095270","https://openalex.org/W1836465849","https://openalex.org/W1964073652","https://openalex.org/W1996118086","https://openalex.org/W2053101950","https://openalex.org/W2064675550","https://openalex.org/W2102409316","https://openalex.org/W2106053110","https://openalex.org/W2117154949","https://openalex.org/W2134738818","https://openalex.org/W2157331557","https://openalex.org/W2164186291","https://openalex.org/W2293634267","https://openalex.org/W2397306716","https://openalex.org/W2525487527","https://openalex.org/W2554891422","https://openalex.org/W2558193840","https://openalex.org/W2603304445","https://openalex.org/W2619383789","https://openalex.org/W2743916180","https://openalex.org/W2783074568","https://openalex.org/W2786768213","https://openalex.org/W2897051344","https://openalex.org/W2900802124","https://openalex.org/W2905837515","https://openalex.org/W2912817382","https://openalex.org/W2946165673","https://openalex.org/W2985076077","https://openalex.org/W3021068338","https://openalex.org/W3036643472","https://openalex.org/W3089557188","https://openalex.org/W3102856398","https://openalex.org/W6675401909","https://openalex.org/W6675751002","https://openalex.org/W6677328822"],"related_works":["https://openalex.org/W2102148524","https://openalex.org/W2314720829","https://openalex.org/W172281880","https://openalex.org/W4385074335","https://openalex.org/W2379392295","https://openalex.org/W3160965418","https://openalex.org/W613940353","https://openalex.org/W2099606355","https://openalex.org/W2355730941","https://openalex.org/W2043960970"],"abstract_inverted_index":{"Vigilance":[0],"estimation":[1,37],"of":[2,9,38,42,51,94,118],"drivers":[3],"is":[4,26,103,112,191],"a":[5,30,59,75,85,115,165,205,213],"hot":[6],"research":[7],"field":[8],"current":[10],"traffic":[11],"safety.":[12],"Wearable":[13],"devices":[14],"can":[15,122,138],"monitor":[16],"information":[17],"regarding":[18],"the":[19,43,49,109,125,133,144,150,160,189,194,198],"driver's":[20],"state":[21],"in":[22,143,159],"real":[23],"time,":[24],"which":[25,92,121],"then":[27],"analyzed":[28],"by":[29,105,114],"data":[31,44,130,178],"analysis":[32,45],"model":[33,46,73,172],"to":[34,78,83,155],"provide":[35],"an":[36],"vigilance.":[39],"The":[40,100,175,202],"accuracy":[41],"directly":[47],"affects":[48],"effect":[50],"vigilance":[52],"estimation.":[53],"In":[54,153],"this":[55],"paper,":[56],"we":[57],"propose":[58],"deep":[60],"coupling":[61,76],"recurrent":[62,168],"auto-encoder":[63,171],"(DCRA)":[64],"that":[65,132,188],"combines":[66],"electroencephalography":[67],"(EEG)":[68],"and":[69,97,108,181,197,212],"electrooculography":[70],"(EOG).":[71],"This":[72],"uses":[74],"layer":[77],"connect":[79],"two":[80],"single-modal":[81,95,101,195],"auto-encoders":[82],"construct":[84],"joint":[86],"objective":[87],"loss":[88,96,102,111],"function":[89],"optimization":[90],"model,":[91],"consists":[93],"multi-modal":[98,110,200],"loss.":[99],"measured":[104,113],"Euclidean":[106],"distance,":[107],"Mahalanobis":[116],"distance":[117,126,134],"metric":[119,151],"learning,":[120],"effectively":[123],"reflect":[124],"between":[127,135],"different":[128,136],"modal":[129],"so":[131],"modes":[137],"be":[139],"described":[140],"more":[141],"accurately":[142],"new":[145],"feature":[146,179,182],"space":[147],"based":[148],"on":[149],"matrix.":[152],"order":[154],"ensure":[156],"gradient":[157],"stability":[158],"long":[161],"sequence":[162],"learning":[163],"process,":[164],"multi-layer":[166],"gated":[167],"unit":[169],"(GRU)":[170],"was":[173],"adopted.":[174],"DCRA":[176,190,203],"integrates":[177],"extraction":[180],"fusion.":[183,201],"Relevant":[184],"comparative":[185],"experiments":[186],"show":[187],"better":[192],"than":[193],"method":[196],"latest":[199],"has":[204],"lower":[206],"root":[207],"mean":[208],"square":[209],"error":[210],"(RMSE)":[211],"higher":[214],"Pearson":[215],"correlation":[216],"coefficient":[217],"(PCC).":[218]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":6}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}
