{"id":"https://openalex.org/W4200189263","doi":"https://doi.org/10.1109/biocas49922.2021.9645009","title":"Residual Learning Attention CNN for Motion Intention Recognition Based on EEG Data","display_name":"Residual Learning Attention CNN for Motion Intention Recognition Based on EEG Data","publication_year":2021,"publication_date":"2021-10-07","ids":{"openalex":"https://openalex.org/W4200189263","doi":"https://doi.org/10.1109/biocas49922.2021.9645009"},"language":"en","primary_location":{"id":"doi:10.1109/biocas49922.2021.9645009","is_oa":false,"landing_page_url":"https://doi.org/10.1109/biocas49922.2021.9645009","pdf_url":null,"source":{"id":"https://openalex.org/S4363608526","display_name":"2021 IEEE Biomedical Circuits and Systems Conference (BioCAS)","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":"2021 IEEE Biomedical Circuits and Systems Conference (BioCAS)","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/A5100427888","display_name":"Ting Wang","orcid":"https://orcid.org/0000-0001-6355-800X"},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ting Wang","raw_affiliation_strings":["Institute of automation, Chinese academy of sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of automation, Chinese academy of sciences, Beijing, China","institution_ids":["https://openalex.org/I4210094879"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020661151","display_name":"Jingna Mao","orcid":"https://orcid.org/0000-0003-4201-8340"},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingna Mao","raw_affiliation_strings":["Institute of automation, Chinese academy of sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of automation, Chinese academy of sciences, Beijing, China","institution_ids":["https://openalex.org/I4210094879"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060230500","display_name":"Ruozhou Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruozhou Xiao","raw_affiliation_strings":["Institute of automation, Chinese academy of sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of automation, Chinese academy of sciences, Beijing, China","institution_ids":["https://openalex.org/I4210094879"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050245647","display_name":"Wuqi Wang","orcid":"https://orcid.org/0009-0009-2028-8711"},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wuqi Wang","raw_affiliation_strings":["Institute of automation, Chinese academy of sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of automation, Chinese academy of sciences, Beijing, China","institution_ids":["https://openalex.org/I4210094879"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058031022","display_name":"Guangxin Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangxin Ding","raw_affiliation_strings":["Institute of automation, Chinese academy of sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of automation, Chinese academy of sciences, Beijing, China","institution_ids":["https://openalex.org/I4210094879"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100347601","display_name":"Zhiwei Zhang","orcid":"https://orcid.org/0000-0002-4766-6198"},"institutions":[{"id":"https://openalex.org/I4210097554","display_name":"Center for Excellence in Brain Science and Intelligence Technology","ror":"https://ror.org/00vpwhm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210097554"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiwei Zhang","raw_affiliation_strings":["CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai, China","Institute of automation, Chinese academy of sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai, China","institution_ids":["https://openalex.org/I4210097554"]},{"raw_affiliation_string":"Institute of automation, Chinese academy of sciences, Beijing, China","institution_ids":["https://openalex.org/I4210094879"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100427888"],"corresponding_institution_ids":["https://openalex.org/I4210094879"],"apc_list":null,"apc_paid":null,"fwci":0.7502,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.61801802,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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":0.9962000250816345,"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":0.9915000200271606,"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":0.8354917764663696},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7869598865509033},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.677901029586792},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6649213433265686},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.6084474921226501},{"id":"https://openalex.org/keywords/brain\u2013computer-interface","display_name":"Brain\u2013computer interface","score":0.5884418487548828},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5110107660293579},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4894229471683502},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45509669184684753},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4496746361255646},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.44186657667160034},{"id":"https://openalex.org/keywords/motor-imagery","display_name":"Motor imagery","score":0.4324491024017334},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4291730523109436},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.12704652547836304}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8354917764663696},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7869598865509033},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.677901029586792},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6649213433265686},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.6084474921226501},{"id":"https://openalex.org/C173201364","wikidata":"https://www.wikidata.org/wiki/Q897410","display_name":"Brain\u2013computer interface","level":3,"score":0.5884418487548828},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5110107660293579},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4894229471683502},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45509669184684753},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4496746361255646},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.44186657667160034},{"id":"https://openalex.org/C54808283","wikidata":"https://www.wikidata.org/wiki/Q6918191","display_name":"Motor imagery","level":4,"score":0.4324491024017334},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4291730523109436},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.12704652547836304},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/biocas49922.2021.9645009","is_oa":false,"landing_page_url":"https://doi.org/10.1109/biocas49922.2021.9645009","pdf_url":null,"source":{"id":"https://openalex.org/S4363608526","display_name":"2021 IEEE Biomedical Circuits and Systems Conference (BioCAS)","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":"2021 IEEE Biomedical Circuits and Systems Conference (BioCAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2010371409","https://openalex.org/W2019780501","https://openalex.org/W2091261861","https://openalex.org/W2108824330","https://openalex.org/W2509948470","https://openalex.org/W2741907166","https://openalex.org/W2888355470","https://openalex.org/W2906965193","https://openalex.org/W2967205117","https://openalex.org/W2996495478","https://openalex.org/W3034528964"],"related_works":["https://openalex.org/W1977940006","https://openalex.org/W2947925238","https://openalex.org/W2887556756","https://openalex.org/W195417223","https://openalex.org/W2951110009","https://openalex.org/W1513407214","https://openalex.org/W1984377984","https://openalex.org/W2510077457","https://openalex.org/W1961545574","https://openalex.org/W3045772920"],"abstract_inverted_index":{"Brain":[0],"computer":[1,61],"interfaces":[2],"(BCIs)":[3],"recognize":[4,75],"users'":[5],"intentions":[6],"to":[7,74,107,160,232],"directly":[8],"control":[9],"the":[10,27,55,83,148,176,197,200,205,216,224,234],"external":[11],"environment":[12],"or":[13,93],"devices.":[14],"Thus,":[15],"accuracy":[16,84,203],"and":[17,38,63,169,179,192,211,221],"robustness":[18],"of":[19,29,57,71,85,96,157,164,204,236],"decoding":[20,130,177],"algorithms":[21,32,178],"have":[22],"an":[23],"essential":[24],"effect":[25],"on":[26,34,88,133,147,196],"performance":[28],"BCIs.":[30,183],"Traditional":[31],"depend":[33],"manually":[35],"extracting":[36],"features":[37],"updating":[39],"parameters":[40],"in":[41,50,60,112,182,189],"various":[42],"experimental":[43],"conditions,":[44],"which":[45,173,214],"limit":[46],"BCI":[47],"paradigm":[48],"application":[49],"reality.":[51],"Nowadays,":[52],"inspired":[53],"by":[54,218,228],"success":[56],"deep":[58],"learning":[59,99],"vision":[62],"speech":[64],"recognition":[65,152],"applications,":[66],"scientific":[67],"researchers":[68],"take":[69],"advantages":[70],"convolutional":[72,89],"networks":[73,90],"EEG":[76,129,165],"motion":[77,117,150],"intention":[78,118,151],"with":[79,186],"superior":[80],"performance.":[81],"Although":[82],"methods":[86],"based":[87,132,146],"can":[91,174],"reach":[92],"exceed":[94],"that":[95],"traditional":[97],"machine":[98],"methods,":[100],"it":[101],"is":[102,144,159,208],"still":[103],"not":[104],"high":[105],"enough":[106],"guarantee":[108],"widespread":[109],"application,":[110],"especially":[111],"complex":[113],"tasks,":[114],"like":[115],"multi-dimension":[116],"recognition.":[119],"In":[120],"this":[121],"paper,":[122],"we":[123],"propose":[124],"a":[125],"novel":[126],"motor":[127],"imagery":[128],"method":[131,207],"Residual":[134],"Learning":[135],"Attention":[136],"Convolutional":[137],"Neural":[138],"Network":[139],"(RLA-CNN).":[140],"First,":[141],"RLA-CNN":[142,158,229],"architecture":[143],"demonstrated":[145],"formulated":[149],"problem.":[153],"The":[154],"basic":[155],"idea":[156],"learn":[161],"attention":[162,225],"weights":[163,226],"channel,":[166],"time":[167],"points,":[168],"feature":[170],"maps":[171],"automatically,":[172],"simplify":[175],"working":[180],"electrodes":[181],"Second,":[184],"Compared":[185],"previous":[187],"work":[188],"four,":[190],"three,":[191],"two":[193],"classes":[194],"tasks":[195],"same":[198],"dataset,":[199],"average":[201],"validation":[202],"proposed":[206],"75.85%,":[209],"84.81%,":[210],"84.69%":[212],"respectively,":[213],"outperforms":[215],"state-of-the-art":[217],"5.65%,":[219],"10.06%,":[220],"7.41%.":[222],"Finally,":[223],"learned":[227],"are":[230],"visualized":[231],"explain":[233],"effectiveness":[235],"RLA-CNN.":[237]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}