{"id":"https://openalex.org/W3013239137","doi":"https://doi.org/10.1109/icnc47757.2020.9049689","title":"Robust EEG-based Emotion Recognition using Multi-feature Joint Sparse Representation","display_name":"Robust EEG-based Emotion Recognition using Multi-feature Joint Sparse Representation","publication_year":2020,"publication_date":"2020-02-01","ids":{"openalex":"https://openalex.org/W3013239137","doi":"https://doi.org/10.1109/icnc47757.2020.9049689","mag":"3013239137"},"language":"en","primary_location":{"id":"doi:10.1109/icnc47757.2020.9049689","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnc47757.2020.9049689","pdf_url":null,"source":{"id":"https://openalex.org/S4306498707","display_name":"2020 International Conference on Computing, Networking and Communications (ICNC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Computing, Networking and Communications (ICNC)","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/A5100416785","display_name":"Dapeng Wu","orcid":"https://orcid.org/0000-0003-2105-9418"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dapeng Wu","raw_affiliation_strings":["School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001947142","display_name":"Xiaojuan Han","orcid":"https://orcid.org/0000-0003-4346-1184"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojuan Han","raw_affiliation_strings":["School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100419573","display_name":"Honggang Wang","orcid":"https://orcid.org/0000-0001-9475-2630"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Honggang Wang","raw_affiliation_strings":["School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015476236","display_name":"Ruyan Wang","orcid":"https://orcid.org/0000-0003-3109-4807"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruyan Wang","raw_affiliation_strings":["School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I10535382"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100416785"],"corresponding_institution_ids":["https://openalex.org/I10535382"],"apc_list":null,"apc_paid":null,"fwci":0.9298,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.65617978,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"34","issue":null,"first_page":"802","last_page":"807"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9988999962806702,"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":0.9988999962806702,"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":0.9986000061035156,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.8079578876495361},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7539045214653015},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7259433269500732},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6309771537780762},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5812088251113892},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5286814570426941},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.5208876132965088},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5168343186378479},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4787170886993408}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.8079578876495361},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7539045214653015},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7259433269500732},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6309771537780762},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5812088251113892},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5286814570426941},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.5208876132965088},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5168343186378479},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4787170886993408},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icnc47757.2020.9049689","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnc47757.2020.9049689","pdf_url":null,"source":{"id":"https://openalex.org/S4306498707","display_name":"2020 International Conference on Computing, Networking and Communications (ICNC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Computing, Networking and Communications (ICNC)","raw_type":"proceedings-article"},{"id":"mag:3088806174","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002233585270338","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","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":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1947251450","https://openalex.org/W1971386783","https://openalex.org/W1985409598","https://openalex.org/W2002055708","https://openalex.org/W2008340903","https://openalex.org/W2019312772","https://openalex.org/W2036309320","https://openalex.org/W2072787788","https://openalex.org/W2081420711","https://openalex.org/W2125478398","https://openalex.org/W2149628368","https://openalex.org/W2169535263","https://openalex.org/W2170883741","https://openalex.org/W2290928405","https://openalex.org/W2337522860","https://openalex.org/W2507248126","https://openalex.org/W2625929003","https://openalex.org/W2746986823","https://openalex.org/W2756474810","https://openalex.org/W2790404832","https://openalex.org/W2806925798","https://openalex.org/W2911220936","https://openalex.org/W2920966660","https://openalex.org/W2994831951","https://openalex.org/W4236533540","https://openalex.org/W6679057767","https://openalex.org/W6760505087","https://openalex.org/W6771432604"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W2104657898","https://openalex.org/W1948992892","https://openalex.org/W1886884218","https://openalex.org/W1910826599","https://openalex.org/W2012353789","https://openalex.org/W2530420969","https://openalex.org/W2051187167","https://openalex.org/W1980100242"],"abstract_inverted_index":{"The":[0],"key":[1],"problem":[2],"of":[3,91,125,152],"emotion":[4,29,59],"recognition":[5,30,53,60,150],"lie":[6],"in":[7],"effective":[8],"electroencephalography":[9],"(EEG)":[10],"signal":[11],"processing":[12],"and":[13,40,94,104,119],"feature":[14,21,36,42,49,72,84],"extraction.":[15],"Traditional":[16],"methods":[17],"mostly":[18],"extract":[19],"single":[20,35],"or":[22],"simply":[23],"combine":[24],"different":[25,96],"features":[26,98],"together,":[27],"but":[28],"based":[31,62],"merely":[32],"on":[33,63,121],"a":[34,57],"may":[37],"be":[38,45],"unreliable":[39],"simple":[41,71],"combination":[43],"will":[44],"affected":[46],"by":[47],"complex":[48],"interdependencies.":[50],"To":[51],"improve":[52],"accuracy,":[54],"we":[55,130],"propose":[56],"multi-feature":[58,111,144],"method":[61],"Joint":[64],"Sparse":[65],"Representation":[66],"(JSR)":[67],"to":[68,87,109,115,136],"transform":[69],"the":[70,89,160],"fusion":[73,112,145],"into":[74],"an":[75,148],"optimization":[76],"problem.":[77],"Specifically,":[78],"sparse":[79],"matrices":[80],"for":[81],"each":[82],"individual":[83],"are":[85,107],"combined":[86],"obtain":[88],"JSR":[90],"these":[92],"features,":[93],"three":[95],"EEG":[97],"including":[99],"wavelet":[100],"energy,":[101],"Hurst":[102],"index,":[103],"fractal":[105],"dimension":[106],"employed":[108],"produce":[110],"results.":[113],"Due":[114],"high":[116],"computational":[117],"complexity":[118],"restrictions":[120],"kernel":[122],"function":[123],"selection":[124],"Support":[126],"Vector":[127,133],"Machine":[128,134],"(SVM),":[129],"adopt":[131],"Relevance":[132],"(RVM)":[135],"classify":[137],"emotions.":[138],"Simulation":[139],"results":[140],"show":[141],"our":[142],"proposed":[143],"algorithm":[146],"has":[147],"average":[149],"accuracy":[151],"over":[153],"85%,":[154],"which":[155],"is":[156],"8%":[157],"higher":[158],"than":[159],"traditional":[161],"method.":[162]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
