{"id":"https://openalex.org/W7126205003","doi":"https://doi.org/10.1109/thms.2026.3654245","title":"GMCDA: Graph-Based Multisource Conditional Distribution Domain Adaptation Network for EEG Recognition of Emotions","display_name":"GMCDA: Graph-Based Multisource Conditional Distribution Domain Adaptation Network for EEG Recognition of Emotions","publication_year":2026,"publication_date":"2026-01-30","ids":{"openalex":"https://openalex.org/W7126205003","doi":"https://doi.org/10.1109/thms.2026.3654245"},"language":null,"primary_location":{"id":"doi:10.1109/thms.2026.3654245","is_oa":false,"landing_page_url":"https://doi.org/10.1109/thms.2026.3654245","pdf_url":null,"source":{"id":"https://openalex.org/S2476799526","display_name":"IEEE Transactions on Human-Machine Systems","issn_l":"2168-2291","issn":["2168-2291","2168-2305"],"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 Transactions on Human-Machine Systems","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/A5043694321","display_name":"Qingshan She","orcid":"https://orcid.org/0000-0001-5206-9833"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingshan She","raw_affiliation_strings":["School of Automation, Hangzhou Dianzi University, and Zhejiang Provincial Key Laboratory of Brain Computer Collaborative Intelligence Technology and Applications Hangzhou, Zhejiang, China"],"raw_orcid":"https://orcid.org/0000-0001-5206-9833","affiliations":[{"raw_affiliation_string":"School of Automation, Hangzhou Dianzi University, and Zhejiang Provincial Key Laboratory of Brain Computer Collaborative Intelligence Technology and Applications Hangzhou, Zhejiang, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124350695","display_name":"Senda Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Senda Gao","raw_affiliation_strings":["HDU-ITMO Joint Institute, Hangzhou Dianzi University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HDU-ITMO Joint Institute, Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002089077","display_name":"Chenqi Zhang","orcid":"https://orcid.org/0000-0002-3557-3701"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenqi Zhang","raw_affiliation_strings":["HDU-ITMO Joint Institute, Hangzhou Dianzi University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-3557-3701","affiliations":[{"raw_affiliation_string":"HDU-ITMO Joint Institute, Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124357074","display_name":"Feng Fang","orcid":null},"institutions":[{"id":"https://openalex.org/I44461941","display_name":"University of Houston","ror":"https://ror.org/048sx0r50","country_code":"US","type":"education","lineage":["https://openalex.org/I44461941"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Feng Fang","raw_affiliation_strings":["Department of Biomedical Engineering, University of Houston, Houston, TX, USA"],"raw_orcid":"https://orcid.org/0000-0003-1004-7876","affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, University of Houston, Houston, TX, USA","institution_ids":["https://openalex.org/I44461941"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jian Wang","orcid":"https://orcid.org/0000-0002-4593-5809"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Wang","raw_affiliation_strings":["School of Automation, Hangzhou Dianzi University, and Zhejiang Provincial Key Laboratory of Brain Computer Collaborative Intelligence Technology and Applications Hangzhou, Zhejiang, China"],"raw_orcid":"https://orcid.org/0000-0002-4593-5809","affiliations":[{"raw_affiliation_string":"School of Automation, Hangzhou Dianzi University, and Zhejiang Provincial Key Laboratory of Brain Computer Collaborative Intelligence Technology and Applications Hangzhou, Zhejiang, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113970661","display_name":"Anton A. Zhilenkov","orcid":null},"institutions":[{"id":"https://openalex.org/I4210141538","display_name":"State Marine Technical University of St. Petersburg","ror":"https://ror.org/03spdpm68","country_code":"RU","type":"education","lineage":["https://openalex.org/I4210141538"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Anton Zhilenkov","raw_affiliation_strings":["Department of Cyber-Physical Systems, St. Petersburg State Marine Technical University, Saint-Petersburg, Russia"],"raw_orcid":"https://orcid.org/0000-0003-1555-1318","affiliations":[{"raw_affiliation_string":"Department of Cyber-Physical Systems, St. Petersburg State Marine Technical University, Saint-Petersburg, Russia","institution_ids":["https://openalex.org/I4210141538"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124425807","display_name":"Yingchun Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I145608581","display_name":"University of Miami","ror":"https://ror.org/02dgjyy92","country_code":"US","type":"education","lineage":["https://openalex.org/I145608581"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yingchun Zhang","raw_affiliation_strings":["Department of Biomedical Engineering, Desai Sethi Urology Institute, and Miami Project to Cure Paralysis at the University of Miami, Coral Gables, FL, USA"],"raw_orcid":"https://orcid.org/0000-0002-1927-4103","affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, Desai Sethi Urology Institute, and Miami Project to Cure Paralysis at the University of Miami, Coral Gables, FL, USA","institution_ids":["https://openalex.org/I145608581"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12393162,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"56","issue":"2","first_page":"356","last_page":"365"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9003999829292297,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.9003999829292297,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.08900000154972076,"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/T10057","display_name":"Face and Expression Recognition","score":0.0005000000237487257,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.6888999938964844},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5519000291824341},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.46369999647140503},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.46059998869895935},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4537999927997589},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4066999852657318},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.392300009727478},{"id":"https://openalex.org/keywords/conditional-probability-distribution","display_name":"Conditional probability distribution","score":0.36890000104904175}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6959999799728394},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.6888999938964844},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5929999947547913},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5519000291824341},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4823000133037567},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.46369999647140503},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.46059998869895935},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4537999927997589},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4066999852657318},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.392300009727478},{"id":"https://openalex.org/C43555835","wikidata":"https://www.wikidata.org/wiki/Q2300258","display_name":"Conditional probability distribution","level":2,"score":0.36890000104904175},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.3610000014305115},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.35280001163482666},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.34360000491142273},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.33730000257492065},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3253999948501587},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.32330000400543213},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.29280000925064087},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2874000072479248},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.28630000352859497},{"id":"https://openalex.org/C2778023277","wikidata":"https://www.wikidata.org/wiki/Q321703","display_name":"Premise","level":2,"score":0.275299996137619},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26899999380111694},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.2685999870300293},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2599000036716461},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.25099998712539673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/thms.2026.3654245","is_oa":false,"landing_page_url":"https://doi.org/10.1109/thms.2026.3654245","pdf_url":null,"source":{"id":"https://openalex.org/S2476799526","display_name":"IEEE Transactions on Human-Machine Systems","issn_l":"2168-2291","issn":["2168-2291","2168-2305"],"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 Transactions on Human-Machine Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5574733590","display_name":null,"funder_award_id":"62371172","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/F4320327494","display_name":"Ministry of Science and Higher Education of the Russian Federation","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Electroencephalography":[0],"(EEG)":[1],"emotion":[2,64],"recognition":[3,65],"is":[4,11,22,137,159,168],"critical":[5],"in":[6,199,209],"human-computer":[7],"interface":[8],"applications.":[9],"EEG":[10,21,48,88],"a":[12,60,67],"prevalent":[13],"tool":[14],"for":[15,63,109],"discerning":[16],"various":[17],"emotional":[18],"states.":[19],"However,":[20],"confronted":[23],"with":[24,144,214],"the":[25,51,84,101,124,131,145,171,177,185,200,210],"challenges,":[26],"including":[27],"nonstationarity,":[28],"small":[29],"amplitude,":[30],"low":[31],"signal-to-noise":[32],"ratio,":[33],"and":[34,80,121,188,197,207],"significant":[35],"inter-subject":[36],"variability.":[37],"Furthermore,":[38],"existing":[39],"methods":[40],"primarily":[41],"focus":[42],"on":[43,127,176,184],"frequency":[44],"domain":[45,71,136],"features":[46],"of":[47,133],"signal,":[49],"overlooking":[50],"interchannel":[52],"relationships.":[53],"To":[54],"solve":[55],"these":[56,162],"problems,":[57],"we":[58,94,105,180],"introduce":[59],"novel":[61],"approach":[62,76],"using":[66],"graph-based":[68],"conditional":[69,118],"distribution-aligned":[70],"adaptation":[72],"(DA)":[73],"network.":[74],"This":[75],"harmonizes":[77],"both":[78],"domain-invariant":[79,102],"domain-specific":[81,115],"features.":[82,103],"With":[83],"premise":[85],"that":[86],"diverse":[87],"data":[89],"share":[90],"consistent":[91],"underlying":[92],"features,":[93,116],"employ":[95],"dynamic":[96],"graph":[97],"convolution":[98],"to":[99,113,140,152],"extract":[100],"Subsequently,":[104],"build":[106],"separate":[107],"branches":[108],"distinct":[110],"source":[111,135],"domains":[112],"harness":[114],"execute":[117],"distribution":[119,128,142],"alignment,":[120],"eventually":[122],"determine":[123],"scores":[125],"based":[126],"distance.":[129],"Specifically,":[130],"contribution":[132],"each":[134],"weighted":[138,163,173],"according":[139],"its":[141],"similarity":[143],"target":[146],"domain,":[147],"thereby":[148],"assigning":[149],"greater":[150],"importance":[151],"more":[153],"relevant":[154],"sources.":[155],"The":[156,165,191],"final":[157,166],"outcome":[158,167],"obtained":[160],"via":[161,170],"scores.":[164,174],"ascertained":[169],"associated":[172],"Based":[175],"leave-one-out":[178],"cross-validation,":[179],"tested":[181],"our":[182,219],"model":[183],"open-source":[186],"SEED":[187],"SEED-IV":[189],"datasets.":[190],"mean":[192],"accuracy":[193],"rates":[194],"were":[195],"90.33%":[196],"62.83%":[198],"cross-subject":[201],"situation,":[202],"as":[203,205],"well":[204],"93.26%":[206],"67.06%":[208],"cross-session":[211],"situation.":[212],"Compared":[213],"multiple":[215],"state-of-the-art":[216],"DA":[217],"algorithms,":[218],"proposed":[220],"algorithm":[221],"garners":[222],"better":[223],"classification":[224],"results.":[225]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-02-01T00:00:00"}
