{"id":"https://openalex.org/W4408898995","doi":"https://doi.org/10.1109/bci65088.2025.10931656","title":"Feature Selection via Dynamic Graph\u2013Based Attention Block in MI\u2013Based EEG Signals","display_name":"Feature Selection via Dynamic Graph\u2013Based Attention Block in MI\u2013Based EEG Signals","publication_year":2025,"publication_date":"2025-02-24","ids":{"openalex":"https://openalex.org/W4408898995","doi":"https://doi.org/10.1109/bci65088.2025.10931656"},"language":"en","primary_location":{"id":"doi:10.1109/bci65088.2025.10931656","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bci65088.2025.10931656","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 13th International Conference on Brain-Computer Interface (BCI)","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/A5083314040","display_name":"Hyeon-Taek Han","orcid":"https://orcid.org/0000-0002-0374-4916"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Hyeon-Taek Han","raw_affiliation_strings":["Korea University,Dept. of Artificial Intelligence,Seoul,Korea"],"affiliations":[{"raw_affiliation_string":"Korea University,Dept. of Artificial Intelligence,Seoul,Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007757156","display_name":"Dae-Hyeok Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dae-Hyeok Lee","raw_affiliation_strings":["Korea University,Dept. of Brain and Cognitive Engineering,Seoul,Korea"],"affiliations":[{"raw_affiliation_string":"Korea University,Dept. of Brain and Cognitive Engineering,Seoul,Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070086344","display_name":"Heon-Gyu Kwak","orcid":null},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Heon-Gyu Kwak","raw_affiliation_strings":["Korea University,Dept. of Artificial Intelligence,Seoul,Korea"],"affiliations":[{"raw_affiliation_string":"Korea University,Dept. of Artificial Intelligence,Seoul,Korea","institution_ids":["https://openalex.org/I197347611"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5083314040"],"corresponding_institution_ids":["https://openalex.org/I197347611"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06814416,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9902999997138977,"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":0.9902999997138977,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9603999853134155,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9567000269889832,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/computer-science","display_name":"Computer science","score":0.7105262875556946},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.6492059826850891},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6335552930831909},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5851523280143738},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5510802268981934},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5429711937904358},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4516162872314453},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.415999174118042},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.34053486585617065},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.1828758418560028},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.06578820943832397},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.05762484669685364}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7105262875556946},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.6492059826850891},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6335552930831909},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5851523280143738},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5510802268981934},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5429711937904358},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4516162872314453},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.415999174118042},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.34053486585617065},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1828758418560028},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.06578820943832397},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.05762484669685364},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bci65088.2025.10931656","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bci65088.2025.10931656","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 13th International Conference on Brain-Computer Interface (BCI)","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":22,"referenced_works":["https://openalex.org/W1486572897","https://openalex.org/W1973052738","https://openalex.org/W2076196856","https://openalex.org/W2128909182","https://openalex.org/W2133999722","https://openalex.org/W2151669316","https://openalex.org/W2505613605","https://openalex.org/W2559463885","https://openalex.org/W2741907166","https://openalex.org/W2804035092","https://openalex.org/W2804658738","https://openalex.org/W2989793251","https://openalex.org/W2997849943","https://openalex.org/W3007994488","https://openalex.org/W3040262915","https://openalex.org/W3171139701","https://openalex.org/W3212535881","https://openalex.org/W4294811271","https://openalex.org/W4319068569","https://openalex.org/W4362681503","https://openalex.org/W4385327052","https://openalex.org/W6963588625"],"related_works":["https://openalex.org/W2922348724","https://openalex.org/W200322357","https://openalex.org/W2130428257","https://openalex.org/W4308951944","https://openalex.org/W2057366091","https://openalex.org/W4312960290","https://openalex.org/W2049513647","https://openalex.org/W2988848585","https://openalex.org/W4386564352","https://openalex.org/W2952668426"],"abstract_inverted_index":{"Brain-computer":[0],"interface":[1],"(BCI)":[2],"technology":[3],"enables":[4],"direct":[5],"interaction":[6],"between":[7],"humans":[8],"and":[9,47,120,134,170,186],"computers":[10],"by":[11,40],"analyzing":[12],"brain":[13],"signals.":[14],"Electroencephalogram":[15],"(EEG)":[16],"is":[17],"one":[18],"of":[19,76,115,148,193],"the":[20,74,77,92,116,136,140,144,154,158,162,166,168,171,178,183],"non-invasive":[21],"tools":[22],"used":[23],"in":[24,52],"BCI":[25,149],"systems,":[26],"providing":[27],"high":[28],"temporal":[29],"resolution":[30],"for":[31],"real-time":[32],"applications.":[33],"However,":[34],"EEG":[35,60,126],"signals":[36,61],"are":[37],"often":[38],"affected":[39],"a":[41],"low":[42,66,106],"signal-to-noise":[43],"ratio,":[44],"physiological":[45],"artifacts,":[46],"individual":[48],"variability,":[49],"representing":[50],"challenges":[51],"extracting":[53],"distinct":[54],"features.":[55,85],"Also,":[56],"motor":[57],"imagery":[58],"(MI)-based":[59],"could":[62,181,203],"contain":[63],"features":[64,104,133,206],"with":[65,105],"correlation":[67,107],"to":[68,80,108,123,129,152,188,208],"MI":[69,100,109,194,209],"characteristics,":[70],"which":[71],"might":[72],"cause":[73],"weights":[75],"deep":[78,94],"model":[79],"become":[81],"biased":[82],"towards":[83],"those":[84],"To":[86],"address":[87],"these":[88],"problems,":[89],"we":[90,197],"proposed":[91,112,141,159,179,201],"end-to-end":[93],"preprocessing":[95],"method":[96,113,142,160,180,202],"that":[97,177,199],"effectively":[98],"enhances":[99],"characteristics":[101],"while":[102],"attenuating":[103],"characteristics.":[110,210],"The":[111,173],"consisted":[114],"temporal,":[117],"spatial,":[118],"graph,":[119],"similarity":[121],"blocks":[122],"preprocess":[124],"MI-based":[125],"signals,":[127],"aiming":[128],"extract":[130],"more":[131,189],"discriminative":[132,205],"improve":[135],"robustness.":[137],"We":[138],"evaluated":[139],"using":[143],"public":[145],"dataset":[146],"2a":[147],"Competition":[150],"IV":[151],"compare":[153],"performances":[155,185],"when":[156],"integrating":[157],"into":[161],"conventional":[163],"models,":[164],"including":[165],"DeepConvNet,":[167],"M-ShallowConvNet,":[169],"EEGNet.":[172],"experimental":[174],"results":[175],"showed":[176],"achieve":[182],"improved":[184],"lead":[187],"clustered":[190],"feature":[191],"distributions":[192],"tasks.":[195],"Hence,":[196],"demonstrated":[198],"our":[200],"enhance":[204],"related":[207]},"counts_by_year":[],"updated_date":"2025-12-19T19:40:27.379048","created_date":"2025-10-10T00:00:00"}
