{"id":"https://openalex.org/W3006673474","doi":"https://doi.org/10.1109/access.2020.2974009","title":"Emotion Recognition From Multi-Channel EEG Signals by Exploiting the Deep Belief-Conditional Random Field Framework","display_name":"Emotion Recognition From Multi-Channel EEG Signals by Exploiting the Deep Belief-Conditional Random Field Framework","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3006673474","doi":"https://doi.org/10.1109/access.2020.2974009","mag":"3006673474"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.2974009","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2974009","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08999626.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08999626.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021932420","display_name":"Chao Hao","orcid":"https://orcid.org/0000-0001-6700-9446"},"institutions":[{"id":"https://openalex.org/I4210166499","display_name":"Henan Polytechnic University","ror":"https://ror.org/05vr1c885","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210166499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Chao","raw_affiliation_strings":["School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, China"],"raw_orcid":"https://orcid.org/0000-0001-6700-9446","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, China","institution_ids":["https://openalex.org/I4210166499"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101746424","display_name":"Yongli Liu","orcid":"https://orcid.org/0000-0002-0540-865X"},"institutions":[{"id":"https://openalex.org/I4210166499","display_name":"Henan Polytechnic University","ror":"https://ror.org/05vr1c885","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210166499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongli Liu","raw_affiliation_strings":["School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, China"],"raw_orcid":"https://orcid.org/0000-0002-0540-865X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, China","institution_ids":["https://openalex.org/I4210166499"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210166499"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":6.9132,"has_fulltext":true,"cited_by_count":60,"citation_normalized_percentile":{"value":0.97503245,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"8","issue":null,"first_page":"33002","last_page":"33012"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9993000030517578,"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":0.9993000030517578,"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":0.9987999796867371,"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":0.9955999851226807,"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/conditional-random-field","display_name":"Conditional random field","score":0.7757486701011658},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7042837142944336},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.6604957580566406},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5063480138778687},{"id":"https://openalex.org/keywords/belief-propagation","display_name":"Belief propagation","score":0.49837827682495117},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4808938503265381},{"id":"https://openalex.org/keywords/deep-belief-network","display_name":"Deep belief network","score":0.4580574929714203},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4290945529937744},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.42805081605911255},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.42288699746131897},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2033233642578125},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.20031234622001648},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.14812049269676208},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1257009208202362},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.0806078314781189},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.07584300637245178},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07178527116775513}],"concepts":[{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.7757486701011658},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7042837142944336},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.6604957580566406},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5063480138778687},{"id":"https://openalex.org/C152948882","wikidata":"https://www.wikidata.org/wiki/Q4060686","display_name":"Belief propagation","level":3,"score":0.49837827682495117},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4808938503265381},{"id":"https://openalex.org/C97385483","wikidata":"https://www.wikidata.org/wiki/Q16954980","display_name":"Deep belief network","level":3,"score":0.4580574929714203},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4290945529937744},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.42805081605911255},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.42288699746131897},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2033233642578125},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.20031234622001648},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.14812049269676208},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1257009208202362},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0806078314781189},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.07584300637245178},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07178527116775513},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.2974009","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2974009","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08999626.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:35c235d8f8864c96ae464c0d42ac0d8a","is_oa":true,"landing_page_url":"https://doaj.org/article/35c235d8f8864c96ae464c0d42ac0d8a","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":"IEEE Access, Vol 8, Pp 33002-33012 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.2974009","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2974009","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08999626.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.7699999809265137}],"awards":[{"id":"https://openalex.org/G2906930928","display_name":null,"funder_award_id":"19A520004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4257647170","display_name":null,"funder_award_id":"61502150","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7129771404","display_name":null,"funder_award_id":"NSFRF1616","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8024604275","display_name":null,"funder_award_id":"172102210279","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":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3006673474.pdf","grobid_xml":"https://content.openalex.org/works/W3006673474.grobid-xml"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W1766290689","https://openalex.org/W1947251450","https://openalex.org/W1993882792","https://openalex.org/W1999845678","https://openalex.org/W2002055708","https://openalex.org/W2022795097","https://openalex.org/W2063922127","https://openalex.org/W2064770205","https://openalex.org/W2100495367","https://openalex.org/W2109949839","https://openalex.org/W2130175312","https://openalex.org/W2136922672","https://openalex.org/W2139564752","https://openalex.org/W2158823144","https://openalex.org/W2176865601","https://openalex.org/W2334364997","https://openalex.org/W2344864600","https://openalex.org/W2357216205","https://openalex.org/W2399697877","https://openalex.org/W2565944610","https://openalex.org/W2566837133","https://openalex.org/W2572280252","https://openalex.org/W2572741602","https://openalex.org/W2605367287","https://openalex.org/W2731964405","https://openalex.org/W2755014019","https://openalex.org/W2765362197","https://openalex.org/W2775675437","https://openalex.org/W2799331981","https://openalex.org/W2800893827","https://openalex.org/W2885005742","https://openalex.org/W2893202050","https://openalex.org/W2896667291","https://openalex.org/W2904463929","https://openalex.org/W2944401411","https://openalex.org/W4234031798","https://openalex.org/W6608523365","https://openalex.org/W6637989529","https://openalex.org/W6712734878","https://openalex.org/W6731776189","https://openalex.org/W6731777001","https://openalex.org/W6735963690","https://openalex.org/W6745545904"],"related_works":["https://openalex.org/W2356597680","https://openalex.org/W2093471820","https://openalex.org/W50079190","https://openalex.org/W2114846443","https://openalex.org/W3102147106","https://openalex.org/W2111726165","https://openalex.org/W3006673474","https://openalex.org/W1970507545","https://openalex.org/W2805435330","https://openalex.org/W2009863654"],"abstract_inverted_index":{"Recently,":[0],"much":[1],"attention":[2],"has":[3],"been":[4],"attracted":[5],"to":[6,102,127,144,150,166],"automatic":[7],"emotion":[8,123,147,171,219],"recognition":[9],"based":[10,137],"on":[11,138,176],"multi-channel":[12,89,110],"electroencephalogram":[13],"(EEG)":[14],"signals,":[15],"with":[16,68,232],"the":[17,28,38,49,63,77,79,88,104,109,114,121,128,133,146,156,161,192,203,223,227,240,246,253],"rapid":[18],"development":[19],"of":[20,44,108,200,215,226,245,252],"machine":[21],"learning":[22],"methods.":[23],"However,":[24],"traditional":[25],"methods":[26],"ignore":[27],"correlation":[29,198,210],"information":[30,43,199,211,214],"between":[31],"different":[32],"channels,":[33],"and":[34,41,72,186,206,212],"cannot":[35],"fully":[36],"capture":[37],"long-term":[39],"dependencies":[40],"contextual":[42,213],"EEG":[45,90,111,216],"signals.":[46,112],"To":[47],"address":[48],"problems,":[50],"this":[51,154],"paper":[52],"proposes":[53],"a":[54,93],"deep":[55,65,167,248],"belief-conditional":[56],"random":[57,74,116,163],"field":[58,117,164],"(DBN-CRF)":[59],"framework":[60,194,255],"which":[61,182],"integrates":[62],"improved":[64],"belief":[66,168],"networks":[67,169],"glia":[69,204],"chains":[70,205],"(DBN-GC)":[71],"conditional":[73,115,162],"field.":[75],"In":[76,221],"framework,":[78],"raw":[80],"feature":[81,106,130],"vector":[82],"sequence":[83,107,125],"is":[84,142,155,230,256],"firstly":[85],"extracted":[86],"from":[87],"signals":[91,217],"by":[92,202],"sliding":[94],"window.":[95],"Then,":[96],"parallel":[97],"DBN-GC":[98],"models":[99],"are":[100,174],"utilized":[101],"obtain":[103],"high-level":[105,129],"And":[113],"(CRF)":[118],"model":[119],"generates":[120],"predicted":[122],"label":[124],"according":[126],"sequence.":[131],"Finally,":[132],"decision":[134],"merge":[135],"layer":[136],"K-nearest":[139],"neighbor":[140],"algorithm":[141],"employed":[143],"estimate":[145],"state.":[148],"According":[149],"our":[151],"best":[152],"knowledge,":[153],"first":[157],"attempt":[158],"that":[159,191,239],"applies":[160],"methodology":[165],"for":[170,218],"recognition.":[172,220],"Experiments":[173],"conducted":[175],"three":[177],"publicly":[178],"available":[179],"emotional":[180],"datasets":[181],"include":[183],"AMIGOS,":[184],"SEED":[185],"DEAP.":[187],"The":[188,236],"results":[189,237],"demonstrate":[190],"proposed":[193,228,241,254],"can":[195],"mine":[196],"inter":[197,208],"multiple-channel":[201],"catch":[207],"channel":[209],"addition,":[222],"classification":[224],"accuracy":[225],"method":[229,242],"compared":[231],"several":[233],"classical":[234],"techniques.":[235],"indicate":[238],"outperforms":[243],"most":[244],"other":[247],"classifiers.":[249],"Thus,":[250],"potential":[251],"demonstrated.":[257]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":15},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":4}],"updated_date":"2026-08-12T21:12:35.861297","created_date":"2025-10-10T00:00:00"}