{"id":"https://openalex.org/W4312508188","doi":"https://doi.org/10.1109/iscas48785.2022.9937435","title":"Coupling Convolution, Transformer and Graph Embedding for Motor Imagery Brain-Computer Interfaces","display_name":"Coupling Convolution, Transformer and Graph Embedding for Motor Imagery Brain-Computer Interfaces","publication_year":2022,"publication_date":"2022-05-28","ids":{"openalex":"https://openalex.org/W4312508188","doi":"https://doi.org/10.1109/iscas48785.2022.9937435"},"language":"en","primary_location":{"id":"doi:10.1109/iscas48785.2022.9937435","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas48785.2022.9937435","pdf_url":null,"source":{"id":"https://openalex.org/S4363604393","display_name":"2022 IEEE International Symposium on Circuits and Systems (ISCAS)","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":"2022 IEEE International Symposium on Circuits and Systems (ISCAS)","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/A5088197463","display_name":"Zexu Wu","orcid":"https://orcid.org/0000-0001-7609-9762"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zexu Wu","raw_affiliation_strings":["Tianjin University,School of Electrical and Information Engineering,Tianjin,China,300072"],"affiliations":[{"raw_affiliation_string":"Tianjin University,School of Electrical and Information Engineering,Tianjin,China,300072","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084878606","display_name":"Biao Sun","orcid":"https://orcid.org/0000-0002-4124-9350"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Biao Sun","raw_affiliation_strings":["Tianjin University,School of Electrical and Information Engineering,Tianjin,China,300072"],"affiliations":[{"raw_affiliation_string":"Tianjin University,School of Electrical and Information Engineering,Tianjin,China,300072","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100618811","display_name":"Xinshan Zhu","orcid":"https://orcid.org/0000-0003-2060-9932"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinshan Zhu","raw_affiliation_strings":["Tianjin University,School of Electrical and Information Engineering,Tianjin,China,300072"],"affiliations":[{"raw_affiliation_string":"Tianjin University,School of Electrical and Information Engineering,Tianjin,China,300072","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5088197463"],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":null,"apc_paid":null,"fwci":1.2031,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.78462441,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"404","last_page":"408"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":1.0,"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":1.0,"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/T11601","display_name":"Neuroscience and Neural Engineering","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/2804","display_name":"Cellular and Molecular 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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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":0.7476968765258789},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6800981163978577},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6200522184371948},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5982372164726257},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5639781951904297},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5269378423690796},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5212376713752747},{"id":"https://openalex.org/keywords/motor-imagery","display_name":"Motor imagery","score":0.5065425634384155},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.49451491236686707},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.493852436542511},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.42924267053604126},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4176766574382782},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3539121747016907},{"id":"https://openalex.org/keywords/brain\u2013computer-interface","display_name":"Brain\u2013computer interface","score":0.28991544246673584},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.25104618072509766},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.19603124260902405},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08244502544403076},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.08145380020141602}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7476968765258789},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6800981163978577},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6200522184371948},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5982372164726257},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5639781951904297},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5269378423690796},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5212376713752747},{"id":"https://openalex.org/C54808283","wikidata":"https://www.wikidata.org/wiki/Q6918191","display_name":"Motor imagery","level":4,"score":0.5065425634384155},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.49451491236686707},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.493852436542511},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.42924267053604126},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4176766574382782},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3539121747016907},{"id":"https://openalex.org/C173201364","wikidata":"https://www.wikidata.org/wiki/Q897410","display_name":"Brain\u2013computer interface","level":3,"score":0.28991544246673584},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.25104618072509766},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.19603124260902405},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08244502544403076},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.08145380020141602},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","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},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscas48785.2022.9937435","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas48785.2022.9937435","pdf_url":null,"source":{"id":"https://openalex.org/S4363604393","display_name":"2022 IEEE International Symposium on Circuits and Systems (ISCAS)","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":"2022 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W2093534731","https://openalex.org/W2128404967","https://openalex.org/W2128495200","https://openalex.org/W2557301950","https://openalex.org/W2559463885","https://openalex.org/W2760008660","https://openalex.org/W2792687613","https://openalex.org/W2925836809","https://openalex.org/W2942968344","https://openalex.org/W2960585436","https://openalex.org/W3007612421","https://openalex.org/W3021321823","https://openalex.org/W3046663063","https://openalex.org/W3080395176","https://openalex.org/W3082143837","https://openalex.org/W3098663814","https://openalex.org/W3102455230","https://openalex.org/W3112157188","https://openalex.org/W3119308196","https://openalex.org/W3158014161","https://openalex.org/W3175452902","https://openalex.org/W4385245566","https://openalex.org/W6739901393","https://openalex.org/W6781361515","https://openalex.org/W6782627015","https://openalex.org/W6785386648"],"related_works":["https://openalex.org/W2041547723","https://openalex.org/W4399901117","https://openalex.org/W2081900870","https://openalex.org/W2951280790","https://openalex.org/W2573071966","https://openalex.org/W3100645810","https://openalex.org/W1597963452","https://openalex.org/W4220667112","https://openalex.org/W2060764846","https://openalex.org/W2991940298"],"abstract_inverted_index":{"Over":[0],"the":[1,21,99,113,117],"past":[2],"ten":[3],"years,":[4],"convolution":[5],"neural":[6],"network":[7,56],"(CNN)":[8],"and":[9,66,73,122],"self-attention":[10,39,67],"based":[11,28,40],"models":[12,41],"(e.g.,":[13],"transformer)":[14],"have":[15,110],"shown":[16,111],"extremely":[17],"competitive":[18],"performance":[19,100],"in":[20,126],"classification":[22,95,120],"of":[23,63,101],"motor":[24],"imagery":[25],"(MI)":[26],"tasks":[27],"on":[29,103],"electroencephalogram":[30],"(EEG)":[31],"signals.":[32],"CNN":[33],"exploits":[34],"local":[35,72],"features":[36],"effectively,":[37],"while":[38],"are":[42,84],"good":[43],"at":[44],"capturing":[45],"long-distance":[46],"feature":[47],"dependencies.":[48],"In":[49],"this":[50],"paper,":[51],"we":[52],"propose":[53],"a":[54,88],"hybrid":[55],"structure,":[57],"termed":[58],"TransEEG,":[59],"that":[60,91,112],"takes":[61],"advantage":[62],"convolutional":[64],"operations":[65],"mechanisms":[68],"to":[69,86],"model":[70],"both":[71],"global":[74],"dependencies":[75],"for":[76],"EEG":[77,81],"signal":[78,94],"processing.":[79],"Specifically,":[80],"channel":[82],"relationships":[83],"exploited":[85],"build":[87],"graph":[89],"embedding":[90],"further":[92],"improves":[93],"accuracy.":[96],"We":[97],"evaluated":[98],"TransEEG":[102,114],"two":[104],"datasets":[105],"performed":[106],"MI":[107,119],"movements.":[108],"Experiments":[109],"significantly":[115],"outperformed":[116],"previous":[118],"methods":[121],"achieved":[123],"state-of-the-art":[124],"accuracy":[125],"subject-specifical":[127],"scenario.":[128]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-25T21:42:39.735039","created_date":"2025-10-10T00:00:00"}