{"id":"https://openalex.org/W3209433168","doi":"https://doi.org/10.1109/tim.2021.3124056","title":"Self-Weighted Semi-Supervised Classification for Joint EEG-Based Emotion Recognition and Affective Activation Patterns Mining","display_name":"Self-Weighted Semi-Supervised Classification for Joint EEG-Based Emotion Recognition and Affective Activation Patterns Mining","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3209433168","doi":"https://doi.org/10.1109/tim.2021.3124056","mag":"3209433168"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2021.3124056","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2021.3124056","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","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/A5056881797","display_name":"Yong Peng","orcid":"https://orcid.org/0000-0003-1208-972X"},"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":true,"raw_author_name":"Yong Peng","raw_affiliation_strings":["School of Computer Science and Technology, Hangzhou Dianzi University, and Zhejiang Key Laboratory of Brain-Machine Collaborative Intelligence, Hangzhou 310018, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Hangzhou Dianzi University, and Zhejiang Key Laboratory of Brain-Machine Collaborative Intelligence, Hangzhou 310018, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003649465","display_name":"Wanzeng Kong","orcid":"https://orcid.org/0000-0002-0113-6968"},"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":"Wanzeng Kong","raw_affiliation_strings":["School of Computer Science and Technology, Hangzhou Dianzi University, and Zhejiang Key Laboratory of Brain-Machine Collaborative Intelligence, Hangzhou 310018, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Hangzhou Dianzi University, and Zhejiang Key Laboratory of Brain-Machine Collaborative Intelligence, Hangzhou 310018, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052124467","display_name":"Feiwei Qin","orcid":"https://orcid.org/0000-0001-5036-9365"},"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":"Feiwei Qin","raw_affiliation_strings":["School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003222421","display_name":"Feiping Nie","orcid":"https://orcid.org/0000-0002-0871-6519"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feiping Nie","raw_affiliation_strings":["School of Artificial Intelligence, OPtics and ElectroNics (iOPEN), Northwestern Polytechnical University, Xi\u2019an 710072, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, OPtics and ElectroNics (iOPEN), Northwestern Polytechnical University, Xi\u2019an 710072, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082765502","display_name":"Jinglong Fang","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":"Jinglong Fang","raw_affiliation_strings":["School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China. (e-mail: fjl@hdu.edu.cn)"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China. (e-mail: fjl@hdu.edu.cn)","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040440605","display_name":"Bao\u2010Liang Lu","orcid":"https://orcid.org/0000-0001-8359-0058"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bao-Liang Lu","raw_affiliation_strings":["Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018676117","display_name":"Andrzej Cichocki","orcid":"https://orcid.org/0000-0002-8364-7226"},"institutions":[{"id":"https://openalex.org/I125989756","display_name":"Skolkovo Institute of Science and Technology","ror":"https://ror.org/03f9nc143","country_code":"RU","type":"education","lineage":["https://openalex.org/I125989756"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Andrzej Cichocki","raw_affiliation_strings":["Center for Computational and Data-Intensive Science and Engineering, Skolkov Institute of Science and Technology, Moscow 143026, Russia"],"affiliations":[{"raw_affiliation_string":"Center for Computational and Data-Intensive Science and Engineering, Skolkov Institute of Science and Technology, Moscow 143026, Russia","institution_ids":["https://openalex.org/I125989756"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5056881797"],"corresponding_institution_ids":["https://openalex.org/I50760025"],"apc_list":null,"apc_paid":null,"fwci":3.0867,"has_fulltext":false,"cited_by_count":42,"citation_normalized_percentile":{"value":0.92036809,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"70","issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9998999834060669,"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":0.9998999834060669,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.9998000264167786,"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/T11021","display_name":"ECG Monitoring and Analysis","score":0.9866999983787537,"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/electroencephalography","display_name":"Electroencephalography","score":0.8835921883583069},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6091318726539612},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5815200805664062},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5425423383712769},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5423470735549927},{"id":"https://openalex.org/keywords/session","display_name":"Session (web analytics)","score":0.5345627069473267},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"Emotion classification","score":0.49371156096458435},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.45748794078826904},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4470932185649872},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.41204094886779785},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.221329003572464},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.07394257187843323}],"concepts":[{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.8835921883583069},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6091318726539612},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5815200805664062},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5425423383712769},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5423470735549927},{"id":"https://openalex.org/C2779182362","wikidata":"https://www.wikidata.org/wiki/Q17126187","display_name":"Session (web analytics)","level":2,"score":0.5345627069473267},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.49371156096458435},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.45748794078826904},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4470932185649872},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.41204094886779785},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.221329003572464},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.07394257187843323},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2021.3124056","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2021.3124056","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.5199999809265137}],"awards":[{"id":"https://openalex.org/G1926699777","display_name":null,"funder_award_id":"LY21F030005","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"},{"id":"https://openalex.org/G2018635161","display_name":null,"funder_award_id":"19ZDA348","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2934698542","display_name":null,"funder_award_id":"61972121","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3275633148","display_name":null,"funder_award_id":"2017M620470","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G3474571101","display_name":null,"funder_award_id":"61971173","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4855704636","display_name":null,"funder_award_id":"LY21F020015","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"},{"id":"https://openalex.org/G6695886218","display_name":null,"funder_award_id":"U20B2074","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7453148966","display_name":null,"funder_award_id":"GD21202","funder_id":"https://openalex.org/F4320317318","funder_display_name":"Guangxi Key Laboratory of Optoelectroric Information Processing"}],"funders":[{"id":"https://openalex.org/F4320317318","display_name":"Guangxi Key Laboratory of Optoelectroric Information Processing","ror":null},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320338464","display_name":"Natural Science Foundation of Zhejiang Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W141062567","https://openalex.org/W1947251450","https://openalex.org/W2038610431","https://openalex.org/W2048219658","https://openalex.org/W2081420711","https://openalex.org/W2101751541","https://openalex.org/W2139823104","https://openalex.org/W2144004426","https://openalex.org/W2154053567","https://openalex.org/W2171837816","https://openalex.org/W2398606097","https://openalex.org/W2464929676","https://openalex.org/W2598291992","https://openalex.org/W2739902099","https://openalex.org/W2786768213","https://openalex.org/W2790404832","https://openalex.org/W2796435388","https://openalex.org/W2899642931","https://openalex.org/W2913846632","https://openalex.org/W2948527927","https://openalex.org/W2950162539","https://openalex.org/W2952286992","https://openalex.org/W2962755824","https://openalex.org/W2962905870","https://openalex.org/W2972861020","https://openalex.org/W2980306787","https://openalex.org/W2982126608","https://openalex.org/W3004084925","https://openalex.org/W3040413318","https://openalex.org/W3041698047","https://openalex.org/W3081651508","https://openalex.org/W3087220290","https://openalex.org/W3089475900","https://openalex.org/W3090070438","https://openalex.org/W3108203525","https://openalex.org/W3127935830","https://openalex.org/W3152660099","https://openalex.org/W3162735870","https://openalex.org/W3164305153","https://openalex.org/W4251909552","https://openalex.org/W6605792473","https://openalex.org/W6660089423","https://openalex.org/W6680434193"],"related_works":["https://openalex.org/W4305042383","https://openalex.org/W2546649374","https://openalex.org/W2773396412","https://openalex.org/W1550318927","https://openalex.org/W4380854332","https://openalex.org/W2184859701","https://openalex.org/W4380370144","https://openalex.org/W4386232293","https://openalex.org/W2382178633","https://openalex.org/W2127511193"],"abstract_inverted_index":{"In":[0],"Electroencephalography":[1],"(EEG)-based":[2],"affective":[3,53,83],"brain-computer":[4],"interfaces":[5],"(aBCIs),":[6],"there":[7],"is":[8,29,48],"a":[9,67,108],"consensus":[10],"that":[11,34,173],"EEG":[12,28,40,116,130,183],"features":[13,117],"extracted":[14],"from":[15,98],"different":[16,22,44,99],"frequency":[17,131,176],"bands":[18,132],"and":[19,32,82,95,119,121,133,153,162,181,189],"channels":[20,134,184],"have":[21],"abilities":[23],"in":[24,56,73,164,185],"emotion":[25,58,80,167,198],"expression.":[26],"Besides,":[27],"so":[30],"weak":[31],"non-stationary":[33],"easily":[35],"causes":[36],"distribution":[37],"discrepancies":[38],"for":[39,76,101,196],"data":[41,104,151],"collected":[42],"at":[43],"times;":[45],"therefore,":[46],"it":[47],"necessary":[49],"to":[50,111],"explore":[51],"the":[52,93,113,124,128,138,147,174,179,182],"activation":[54,84,125],"patterns":[55,85,126],"cross-session":[57,79,166,197],"recognition.":[59,199],"To":[60],"address":[61],"these":[62],"two":[63],"problems,":[64],"we":[65],"propose":[66],"self-weighted":[68,109,140],"semi-supervised":[69],"classification":[70],"(SWSC)":[71],"model":[72],"this":[74],"paper":[75],"joint":[77],"EEG-based":[78],"recognition":[81,168],"mining,":[86],"whose":[87],"merits":[88],"include":[89],"1)":[90],"using":[91],"both":[92],"labeled":[94],"unlabeled":[96],"samples":[97],"sessions":[100],"better":[102],"capturing":[103],"characteristics,":[105],"2)":[106],"introducing":[107],"variable":[110],"learn":[112],"importance":[114],"of":[115,159],"adaptively":[118],"quantitatively,":[120],"3)":[122],"mining":[123],"including":[127],"critical":[129],"automatically":[135],"based":[136],"on":[137,146],"learned":[139],"variable.":[141],"Extensive":[142],"experiments":[143],"are":[144,193],"conducted":[145],"benchmark":[148],"SEED_IV":[149],"emotional":[150],"set":[152],"SWSC":[154,171],"obtained":[155],"excellent":[156],"average":[157],"accuracies":[158],"77.40%,":[160],"79.55%":[161],"81.52%":[163],"three":[165],"tasks.":[169],"Moreover,":[170],"identifies":[172],"Gamma":[175],"band":[177],"contributes":[178],"most":[180],"prefrontal,":[186],"left/right":[187],"temporal":[188],"(central)":[190],"parietal":[191],"lobes":[192],"more":[194],"important":[195]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":8}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
