{"id":"https://openalex.org/W2974596145","doi":"https://doi.org/10.1109/access.2019.2941867","title":"Densely Feature Fusion Based on Convolutional Neural Networks for Motor Imagery EEG Classification","display_name":"Densely Feature Fusion Based on Convolutional Neural Networks for Motor Imagery EEG Classification","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2974596145","doi":"https://doi.org/10.1109/access.2019.2941867","mag":"2974596145"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2941867","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2941867","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08840855.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/ielx7/6287639/8600701/08840855.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100724978","display_name":"Donglin Li","orcid":"https://orcid.org/0000-0001-7660-831X"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Donglin Li","raw_affiliation_strings":["School of Information Science and Engineering, Northeastern University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0001-7660-831X","affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100334399","display_name":"Jianhui Wang","orcid":"https://orcid.org/0000-0002-9716-3484"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianhui Wang","raw_affiliation_strings":["School of Information Science and Engineering, Northeastern University, Shenyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002147826","display_name":"Jiacan Xu","orcid":"https://orcid.org/0000-0001-7401-274X"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiacan Xu","raw_affiliation_strings":["School of Information Science and Engineering, Northeastern University, Shenyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027319540","display_name":"Xiaoke Fang","orcid":null},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoke Fang","raw_affiliation_strings":["School of Information Science and Engineering, Northeastern University, Shenyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I9224756"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":4.4311,"has_fulltext":true,"cited_by_count":73,"citation_normalized_percentile":{"value":0.95310635,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"7","issue":null,"first_page":"132720","last_page":"132730"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9925000071525574,"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"}},{"id":"https://openalex.org/T11601","display_name":"Neuroscience and Neural Engineering","score":0.9923999905586243,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.826730489730835},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7905735969543457},{"id":"https://openalex.org/keywords/brain\u2013computer-interface","display_name":"Brain\u2013computer interface","score":0.6670101881027222},{"id":"https://openalex.org/keywords/motor-imagery","display_name":"Motor imagery","score":0.657638669013977},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6488888263702393},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5705024003982544},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5393993258476257},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5215149521827698},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.4613701105117798},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43424105644226074},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4342166781425476},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4206016957759857},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3735990524291992}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.826730489730835},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7905735969543457},{"id":"https://openalex.org/C173201364","wikidata":"https://www.wikidata.org/wiki/Q897410","display_name":"Brain\u2013computer interface","level":3,"score":0.6670101881027222},{"id":"https://openalex.org/C54808283","wikidata":"https://www.wikidata.org/wiki/Q6918191","display_name":"Motor imagery","level":4,"score":0.657638669013977},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6488888263702393},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5705024003982544},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5393993258476257},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5215149521827698},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.4613701105117798},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43424105644226074},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4342166781425476},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4206016957759857},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3735990524291992},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2941867","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2941867","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08840855.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:3d5d790294654b878c2e796de8baa24b","is_oa":true,"landing_page_url":"https://doaj.org/article/3d5d790294654b878c2e796de8baa24b","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 7, Pp 132720-132730 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2941867","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2941867","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08840855.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":"Partnerships for the goals","score":0.44999998807907104,"id":"https://metadata.un.org/sdg/17"}],"awards":[{"id":"https://openalex.org/G8830865568","display_name":null,"funder_award_id":"61733003","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/W2974596145.pdf","grobid_xml":"https://content.openalex.org/works/W2974596145.grobid-xml"},"referenced_works_count":53,"referenced_works":["https://openalex.org/W1661970536","https://openalex.org/W1965769973","https://openalex.org/W1966101191","https://openalex.org/W1969878365","https://openalex.org/W1987551624","https://openalex.org/W1989940636","https://openalex.org/W2003411364","https://openalex.org/W2008344458","https://openalex.org/W2008359193","https://openalex.org/W2010371409","https://openalex.org/W2023168763","https://openalex.org/W2034312116","https://openalex.org/W2047545657","https://openalex.org/W2059915684","https://openalex.org/W2063650318","https://openalex.org/W2090262261","https://openalex.org/W2097772463","https://openalex.org/W2099509424","https://openalex.org/W2100409538","https://openalex.org/W2100874881","https://openalex.org/W2116308679","https://openalex.org/W2119163516","https://openalex.org/W2131321253","https://openalex.org/W2133988362","https://openalex.org/W2135378997","https://openalex.org/W2136897104","https://openalex.org/W2142280324","https://openalex.org/W2144383914","https://openalex.org/W2147174595","https://openalex.org/W2152119085","https://openalex.org/W2165892205","https://openalex.org/W2168500935","https://openalex.org/W2213712841","https://openalex.org/W2253429366","https://openalex.org/W2265056729","https://openalex.org/W2464397079","https://openalex.org/W2557301950","https://openalex.org/W2740113900","https://openalex.org/W2759030247","https://openalex.org/W2767333869","https://openalex.org/W2792434807","https://openalex.org/W2792724009","https://openalex.org/W2888355470","https://openalex.org/W2892542319","https://openalex.org/W2894170005","https://openalex.org/W2900786131","https://openalex.org/W2908603469","https://openalex.org/W2913246999","https://openalex.org/W2925836809","https://openalex.org/W2962699674","https://openalex.org/W2963446712","https://openalex.org/W2963919481","https://openalex.org/W6685893538"],"related_works":["https://openalex.org/W1977940006","https://openalex.org/W2887556756","https://openalex.org/W2947925238","https://openalex.org/W195417223","https://openalex.org/W1513407214","https://openalex.org/W1984377984","https://openalex.org/W1961545574","https://openalex.org/W2510077457","https://openalex.org/W3045772920","https://openalex.org/W2047816336"],"abstract_inverted_index":{"Electroencephalogram":[0],"(EEG)":[1],"signals":[2],"have":[3],"been":[4],"used":[5],"in":[6,29,48,151,179],"the":[7,17,21,30,49,53,62,76,83,88,105,124,137,148,152,159,165,180,188,196,200,221,225],"Brain-computer":[8],"interface":[9],"(BCI)":[10],"technology":[11,43],"to":[12,187,194,220],"implement":[13],"direct":[14],"communication":[15],"between":[16,139],"human":[18],"body":[19],"and":[20,35,64,82,122,142,157,161,228],"outside":[22],"world,":[23],"which":[24,146],"has":[25,44],"important":[26],"application":[27,198],"prospects":[28],"fields":[31],"of":[32,55,66,79,108,133,154,164,199,215,224],"cognitive":[33],"science":[34],"medical":[36],"rehabilitation.":[37],"In":[38,91,192],"recent":[39],"years,":[40],"deep":[41],"learning":[42],"achieved":[45],"remarkable":[46],"results":[47,169,176,214],"BCI":[50,181],"system,":[51],"especially":[52],"using":[54],"convolutional":[56,100,155],"neural":[57,101],"networks":[58,102],"(CNNs)":[59],"frameworks":[60],"for":[61,130],"identification":[63],"analysis":[65],"motor":[67],"imagery":[68],"signals.":[69],"However,":[70],"practical":[71,197],"applications":[72],"are":[73,218],"limited":[74],"by":[75,177],"complex":[77],"process":[78,153],"data":[80,114,184],"representation,":[81],"end-to-end":[84],"method":[85],"will":[86],"deteriorate":[87],"recognition":[89],"results.":[90],"this":[92,131],"paper,":[93],"we":[94,111,206],"propose":[95,112],"a":[96],"densely":[97,125,201],"feature":[98,126,202],"fusion":[99,127,203],"(DFFN).":[103],"Combining":[104],"morphological":[106],"information":[107,149],"EEG":[109],"signals,":[110],"two":[113],"representation":[115],"methods":[116],"with":[117],"low":[118],"complexity,":[119],"then":[120],"design":[121],"optimize":[123],"network":[128,173,204],"framework":[129],"form":[132],"inputs.":[134],"DFFN":[135],"considers":[136,158],"correlation":[138],"adjacent":[140],"layers":[141],"cross":[143],"layer":[144],"features,":[145],"reduces":[147],"loss":[150],"operation":[156],"local":[160],"global":[162,210],"characteristics":[163],"network.":[166],"The":[167,213],"simulation":[168],"showed":[170],"that":[171],"our":[172],"improve":[174],"classification":[175,217],"5%":[178],"competition":[182],"IV-2a":[183],"set":[185],"compare":[186],"ordinary":[189],"CNNs":[190],"framework.":[191],"order":[193],"verify":[195],"framework,":[205],"train":[207],"an":[208],"adaptive":[209],"model":[211,227],"method.":[212],"average":[216],"close":[219],"baseline":[222],"approach":[223],"subject-dependent":[226],"better":[229],"than":[230],"others.":[231]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":21},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}