{"id":"https://openalex.org/W4417472986","doi":"https://doi.org/10.1109/sipaim67325.2025.11283336","title":"Towards Individual Channel Classifiers and Ensemble Methods for Enhanced Motor Imagery BCI Performance","display_name":"Towards Individual Channel Classifiers and Ensemble Methods for Enhanced Motor Imagery BCI Performance","publication_year":2025,"publication_date":"2025-11-18","ids":{"openalex":"https://openalex.org/W4417472986","doi":"https://doi.org/10.1109/sipaim67325.2025.11283336"},"language":null,"primary_location":{"id":"doi:10.1109/sipaim67325.2025.11283336","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sipaim67325.2025.11283336","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 21st International Symposium on Biomedical Image Processing and Analysis (SIPAIM)","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/A5011699333","display_name":"Jaime A. Riascos","orcid":"https://orcid.org/0000-0001-6134-4139"},"institutions":[{"id":"https://openalex.org/I176453806","display_name":"University of Potsdam","ror":"https://ror.org/03bnmw459","country_code":"DE","type":"education","lineage":["https://openalex.org/I176453806"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Jaime A. Riascos-Salas","raw_affiliation_strings":["Potsdam University,Potsdam Embodied Cognition Group (PECoG),Potsdam,Germany"],"affiliations":[{"raw_affiliation_string":"Potsdam University,Potsdam Embodied Cognition Group (PECoG),Potsdam,Germany","institution_ids":["https://openalex.org/I176453806"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114358914","display_name":"Hern\u00e1n Villota","orcid":"https://orcid.org/0000-0002-6061-7104"},"institutions":[{"id":"https://openalex.org/I4210166306","display_name":"Instituci\u00f3n Universitaria de Envigado","ror":"https://ror.org/05jj6ma85","country_code":"CO","type":"education","lineage":["https://openalex.org/I4210166306"]}],"countries":["CO"],"is_corresponding":false,"raw_author_name":"Hernan Villota","raw_affiliation_strings":["Institución Universitaria de Envigado,Faculty of Engineering,Envigado,Colombia"],"affiliations":[{"raw_affiliation_string":"Institución Universitaria de Envigado,Faculty of Engineering,Envigado,Colombia","institution_ids":["https://openalex.org/I4210166306"]}]},{"author_position":"last","author":{"id":null,"display_name":"Marta Molinas","orcid":null},"institutions":[{"id":"https://openalex.org/I204778367","display_name":"Norwegian University of Science and Technology","ror":"https://ror.org/05xg72x27","country_code":"NO","type":"education","lineage":["https://openalex.org/I204778367"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Marta Molinas","raw_affiliation_strings":["Norwegian University of Science and Technology,Department of Engineering Cybernetics,Trondheim,Norway"],"affiliations":[{"raw_affiliation_string":"Norwegian University of Science and Technology,Department of Engineering Cybernetics,Trondheim,Norway","institution_ids":["https://openalex.org/I204778367"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5011699333"],"corresponding_institution_ids":["https://openalex.org/I176453806"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.41976976,"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":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9976999759674072,"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":0.9976999759674072,"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/T10241","display_name":"Functional Brain Connectivity Studies","score":0.0006000000284984708,"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.0003000000142492354,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/brain\u2013computer-interface","display_name":"Brain\u2013computer interface","score":0.7164999842643738},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5956000089645386},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.5888000130653381},{"id":"https://openalex.org/keywords/motor-imagery","display_name":"Motor imagery","score":0.5809000134468079},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4528999924659729},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4406999945640564},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.43939998745918274},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4226999878883362}],"concepts":[{"id":"https://openalex.org/C173201364","wikidata":"https://www.wikidata.org/wiki/Q897410","display_name":"Brain\u2013computer interface","level":3,"score":0.7164999842643738},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.694599986076355},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5956000089645386},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.593999981880188},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5888000130653381},{"id":"https://openalex.org/C54808283","wikidata":"https://www.wikidata.org/wiki/Q6918191","display_name":"Motor imagery","level":4,"score":0.5809000134468079},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4862000048160553},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4528999924659729},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4406999945640564},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.43939998745918274},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4226999878883362},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.36559998989105225},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.3151000142097473},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.3109999895095825},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.3093000054359436},{"id":"https://openalex.org/C121475858","wikidata":"https://www.wikidata.org/wiki/Q2735911","display_name":"Spatial filter","level":2,"score":0.30230000615119934},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29409998655319214},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.2563000023365021},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2513999938964844},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.25119999051094055},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sipaim67325.2025.11283336","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sipaim67325.2025.11283336","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 21st International Symposium on Biomedical Image Processing and Analysis (SIPAIM)","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":14,"referenced_works":["https://openalex.org/W2006082701","https://openalex.org/W2093250287","https://openalex.org/W2132360759","https://openalex.org/W2151669316","https://openalex.org/W2152017481","https://openalex.org/W2154053567","https://openalex.org/W2794345050","https://openalex.org/W3011231084","https://openalex.org/W3111331364","https://openalex.org/W3186240196","https://openalex.org/W4283787798","https://openalex.org/W4310043238","https://openalex.org/W4320912734","https://openalex.org/W4402363877"],"related_works":[],"abstract_inverted_index":{"This":[0,79,119],"study":[1],"introduces":[2],"a":[3,23,47,97,111],"novel":[4],"approach":[5,61],"to":[6,114],"enhance":[7],"Motor":[8],"Imagery":[9],"Brain-Computer":[10],"Interface":[11],"(MI-BCI)":[12],"classification":[13],"by":[14,62],"training":[15],"individual":[16,52,68],"channel":[17,53,117],"classifiers":[18,54,69],"and":[19,40,107,127],"integrating":[20],"them":[21],"with":[22],"stacking":[24],"ensemble.":[25],"Our":[26],"method":[27],"was":[28],"benchmarked":[29],"against":[30],"established":[31],"techniques,":[32],"including":[33],"Filter":[34],"Bank":[35],"Common":[36],"Spatial":[37],"Patterns":[38],"(FBCSP)":[39],"Minimum":[41],"Redundancy":[42],"Maximum":[43],"Relevance":[44],"(mRMR).":[45],"While":[46],"full":[48],"pool":[49],"of":[50,76,101],"256":[51],"initially":[55],"showed":[56],"suboptimal":[57],"performance,":[58],"refining":[59],"the":[60,65],"selecting":[63],"only":[64],"10":[66],"best-performing":[67],"per":[70],"subject":[71],"yielded":[72],"substantial":[73],"accuracy":[74],"improvements":[75],"over":[77],"20%.":[78],"curated":[80],"selection":[81],"consistently":[82],"outperformed":[83],"FBCSP":[84],"and,":[85],"for":[86,123],"some":[87],"subjects,":[88],"even":[89],"mRMR.":[90],"The":[91],"findings":[92],"suggest":[93],"that":[94],"focusing":[95],"on":[96],"personalized,":[98],"high-performing":[99],"subset":[100],"channels":[102],"can":[103],"effectively":[104],"reduce":[105],"inter-":[106],"intra-subject":[108],"variability,":[109],"offering":[110],"robust":[112],"alternative":[113],"traditional":[115],"optimization-based":[116],"selection.":[118],"framework":[120],"holds":[121],"promise":[122],"developing":[124],"more":[125],"adaptable":[126],"effective":[128],"BCI":[129],"systems.":[130]},"counts_by_year":[],"updated_date":"2026-03-25T23:56:10.502304","created_date":"2025-12-18T00:00:00"}