{"id":"https://openalex.org/W4403534817","doi":"https://doi.org/10.1109/icarm62033.2024.10715972","title":"Corrupted EEG Self-Robust Motion Intention Recognition Method with Multi-Graph Fusion Enhanced Convolutional Network*","display_name":"Corrupted EEG Self-Robust Motion Intention Recognition Method with Multi-Graph Fusion Enhanced Convolutional Network*","publication_year":2024,"publication_date":"2024-07-08","ids":{"openalex":"https://openalex.org/W4403534817","doi":"https://doi.org/10.1109/icarm62033.2024.10715972"},"language":"en","primary_location":{"id":"doi:10.1109/icarm62033.2024.10715972","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarm62033.2024.10715972","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Conference on Advanced Robotics and Mechatronics (ICARM)","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/A5090684900","display_name":"Kecheng Shi","orcid":"https://orcid.org/0000-0003-3448-9492"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kecheng Shi","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Automation Engineering,Chengdu,Sichuan,China,611731"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Automation Engineering,Chengdu,Sichuan,China,611731","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006087341","display_name":"Fengjun Mu","orcid":"https://orcid.org/0000-0002-6153-049X"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fengjun Mu","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Automation Engineering,Chengdu,Sichuan,China,611731"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Automation Engineering,Chengdu,Sichuan,China,611731","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100356635","display_name":"Zhe Li","orcid":"https://orcid.org/0000-0002-0519-7434"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhe Li","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Automation Engineering,Chengdu,Sichuan,China,611731"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Automation Engineering,Chengdu,Sichuan,China,611731","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025340321","display_name":"Jianzhi Lyu","orcid":"https://orcid.org/0000-0001-9702-1120"},"institutions":[{"id":"https://openalex.org/I159176309","display_name":"Universit\u00e4t Hamburg","ror":"https://ror.org/00g30e956","country_code":"DE","type":"education","lineage":["https://openalex.org/I159176309"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jianzhi Lyu","raw_affiliation_strings":["University of Hamburg,Department of Informatics,Hamburg,Germany,22527"],"affiliations":[{"raw_affiliation_string":"University of Hamburg,Department of Informatics,Hamburg,Germany,22527","institution_ids":["https://openalex.org/I159176309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007231606","display_name":"Rui Huang","orcid":"https://orcid.org/0000-0001-7231-5042"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Huang","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Automation Engineering,Chengdu,Sichuan,China,611731"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Automation Engineering,Chengdu,Sichuan,China,611731","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065137338","display_name":"Chaobin Zou","orcid":"https://orcid.org/0000-0003-3457-6369"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chaobin Zou","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042965582","display_name":"Hong Cheng","orcid":"https://orcid.org/0000-0001-5532-9530"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Cheng","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Automation Engineering,Chengdu,Sichuan,China,611731"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Automation Engineering,Chengdu,Sichuan,China,611731","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100326970","display_name":"Jianwei Zhang","orcid":"https://orcid.org/0000-0002-7856-5760"},"institutions":[{"id":"https://openalex.org/I159176309","display_name":"Universit\u00e4t Hamburg","ror":"https://ror.org/00g30e956","country_code":"DE","type":"education","lineage":["https://openalex.org/I159176309"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jianwei Zhang","raw_affiliation_strings":["University of Hamburg,Department of Informatics,Hamburg,Germany,22527"],"affiliations":[{"raw_affiliation_string":"University of Hamburg,Department of Informatics,Hamburg,Germany,22527","institution_ids":["https://openalex.org/I159176309"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5090684900"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19051653,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"152","last_page":"158"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9969000220298767,"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":0.9969000220298767,"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9007999897003174,"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":0.7336903810501099},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6080220937728882},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5244422554969788},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.522549569606781},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5165501832962036},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48799389600753784},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4778125584125519},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4035051167011261},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.11207079887390137},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.062415480613708496}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7336903810501099},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6080220937728882},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5244422554969788},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.522549569606781},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5165501832962036},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48799389600753784},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4778125584125519},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4035051167011261},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.11207079887390137},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.062415480613708496},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icarm62033.2024.10715972","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarm62033.2024.10715972","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Conference on Advanced Robotics and Mechatronics (ICARM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1987219048","https://openalex.org/W2119008936","https://openalex.org/W2132360759","https://openalex.org/W2138038313","https://openalex.org/W2151669316","https://openalex.org/W2346353886","https://openalex.org/W2559463885","https://openalex.org/W2619484096","https://openalex.org/W2739229484","https://openalex.org/W2780011893","https://openalex.org/W2802145570","https://openalex.org/W2893628967","https://openalex.org/W2963285578","https://openalex.org/W2964321699","https://openalex.org/W3100188304","https://openalex.org/W3102455230","https://openalex.org/W3202417708","https://openalex.org/W3209603352","https://openalex.org/W3212858769","https://openalex.org/W4200285824","https://openalex.org/W4206107776","https://openalex.org/W4226159128","https://openalex.org/W4293824843","https://openalex.org/W4294975308","https://openalex.org/W4295517390","https://openalex.org/W4321614376","https://openalex.org/W4379055511","https://openalex.org/W6631190155","https://openalex.org/W6685562342","https://openalex.org/W6720006811"],"related_works":["https://openalex.org/W2922348724","https://openalex.org/W200322357","https://openalex.org/W2130428257","https://openalex.org/W4308951944","https://openalex.org/W4293226380","https://openalex.org/W2057366091","https://openalex.org/W4312960290","https://openalex.org/W2049513647","https://openalex.org/W2988848585","https://openalex.org/W4233722919"],"abstract_inverted_index":{"Motor":[0],"imagery":[1],"brain-computer":[2],"interfaces":[3],"(MI-BCI)":[4],"are":[5,178],"a":[6,62,75,93],"promising":[7],"emerging":[8],"technique":[9],"in":[10,120,152],"hemiplegia":[11],"rehabilitation":[12],"training.":[13],"However,":[14],"the":[15,31,82,85,118,121,153,176],"collected":[16],"electroencephalogram":[17],"(EEG)":[18],"data":[19,27,33,50,89],"from":[20,36],"real-world":[21],"scenarios":[22],"contains":[23],"notable":[24,86],"noise":[25,87],"and":[26,30,52,88,92,104,127,150,155],"channels":[28,177],"missing,":[29,91],"MI-EEG":[32],"varies":[34],"significantly":[35,139],"subject":[37],"to":[38,45,49,56,80,101,116],"subject.":[39],"It":[40],"requires":[41],"BCI":[42],"decoding":[43],"methods":[44],"have":[46],"higher":[47],"robustness":[48,83,160],"defects":[51],"good":[53],"generalization":[54],"ability":[55],"new":[57],"subjects.":[58],"This":[59],"paper":[60],"proposes":[61],"Multi-Graph":[63],"Fusion":[64],"Enhanced":[65],"Network":[66],"(MGFENet)":[67],"for":[68,113],"motion":[69],"intention":[70],"recognition.":[71],"The":[72,159],"MGFENet":[73],"establishes":[74],"dynamic":[76],"channel":[77,90],"selection":[78],"module":[79],"enhance":[81],"of":[84,124,148,170,175],"graph":[94],"fusion-enhanced":[95],"convolutional":[96],"neural":[97],"network":[98],"is":[99],"proposed":[100],"extract":[102],"personalized":[103],"shared":[105],"spatial":[106],"topological":[107],"features":[108],"under":[109],"different":[110,114,125],"frequency":[111],"bands":[112],"subjects,":[115],"accommodate":[117],"differences":[119],"MI":[122],"process":[123],"subjects":[126],"commonalities.":[128],"Extensive":[129],"experiments":[130],"on":[131],"one":[132],"challenging":[133],"benchmark":[134],"show":[135],"that":[136,163],"our":[137,164],"approach":[138,165],"outperforms":[140],"previous":[141],"methods,":[142],"which":[143],"can":[144,166],"archive":[145],"an":[146,168],"accuracy":[147,169],"68.73%":[149],"58.04%":[151],"within-subject":[154],"cross-subject":[156],"cases,":[157],"respectively.":[158],"analysis":[161],"demonstrates":[162],"maintain":[167],"60.41%":[171],"even":[172],"when":[173],"half":[174],"corrupted.":[179]},"counts_by_year":[],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}
