{"id":"https://openalex.org/W7125908372","doi":"https://doi.org/10.1109/smc58881.2025.11343651","title":"Learnable Frequency-Weighting Layer for Improving EEG-Based BCI Performance","display_name":"Learnable Frequency-Weighting Layer for Improving EEG-Based BCI Performance","publication_year":2025,"publication_date":"2025-10-05","ids":{"openalex":"https://openalex.org/W7125908372","doi":"https://doi.org/10.1109/smc58881.2025.11343651"},"language":null,"primary_location":{"id":"doi:10.1109/smc58881.2025.11343651","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11343651","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5120169311","display_name":"Tsu-Jen Ding","orcid":"https://orcid.org/0000-0002-7800-9051"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Tsu-Jen Ding","raw_affiliation_strings":["National Tsing Hua University,Department of Environmental and Cultural Resources,Hsinchu,Taiwan"],"affiliations":[{"raw_affiliation_string":"National Tsing Hua University,Department of Environmental and Cultural Resources,Hsinchu,Taiwan","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121776688","display_name":"Hui-Yu Hsu","orcid":null},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hui-Yu Hsu","raw_affiliation_strings":["National Tsing Hua University,Graduate Institute of Mathematics and Science Education,Hsinchu,Taiwan"],"affiliations":[{"raw_affiliation_string":"National Tsing Hua University,Graduate Institute of Mathematics and Science Education,Hsinchu,Taiwan","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053702420","display_name":"P. C. Kuo","orcid":"https://orcid.org/0000-0001-9958-2204"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Po-Chih Kuo","raw_affiliation_strings":["National Tsing Hua University,Department of Computer Science,Hsinchu,Taiwan"],"affiliations":[{"raw_affiliation_string":"National Tsing Hua University,Department of Computer Science,Hsinchu,Taiwan","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123300418","display_name":"Zai-Fu Yao","orcid":null},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Zai-Fu Yao","raw_affiliation_strings":["National Tsing Hua University,Department of Educational Psychology and Counseling,Hsinchu,Taiwan"],"affiliations":[{"raw_affiliation_string":"National Tsing Hua University,Department of Educational Psychology and Counseling,Hsinchu,Taiwan","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020731998","display_name":"C. H. Pan","orcid":null},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Cheng-Yu Pan","raw_affiliation_strings":["National Tsing Hua University,Graduate Institute of Mathematics and Science Education,Hsinchu,Taiwan"],"affiliations":[{"raw_affiliation_string":"National Tsing Hua University,Graduate Institute of Mathematics and Science Education,Hsinchu,Taiwan","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101258317","display_name":"Bo-Yu Pan","orcid":null},"institutions":[{"id":"https://openalex.org/I185940356","display_name":"Soochow University","ror":"https://ror.org/05kvm7n82","country_code":"TW","type":"education","lineage":["https://openalex.org/I185940356"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Bo-Yu Pan","raw_affiliation_strings":["Soochow University,Department of Mathematics,Taipei,Taiwan"],"affiliations":[{"raw_affiliation_string":"Soochow University,Department of Mathematics,Taipei,Taiwan","institution_ids":["https://openalex.org/I185940356"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5120169311"],"corresponding_institution_ids":["https://openalex.org/I25846049"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.75243213,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6885","last_page":"6890"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.995199978351593,"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":0.995199978351593,"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":0.0005000000237487257,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.0005000000237487257,"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/brain\u2013computer-interface","display_name":"Brain\u2013computer interface","score":0.7117000222206116},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.5393000245094299},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5325999855995178},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.5296000242233276},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4812000095844269},{"id":"https://openalex.org/keywords/cognition","display_name":"Cognition","score":0.4627000093460083},{"id":"https://openalex.org/keywords/interface","display_name":"Interface (matter)","score":0.43650001287460327},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4309000074863434}],"concepts":[{"id":"https://openalex.org/C173201364","wikidata":"https://www.wikidata.org/wiki/Q897410","display_name":"Brain\u2013computer interface","level":3,"score":0.7117000222206116},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6902999877929688},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.5393000245094299},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5376999974250793},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5325999855995178},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.5296000242233276},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4812000095844269},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.4627000093460083},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.43650001287460327},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4309000074863434},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.4230000078678131},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3919000029563904},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3361999988555908},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.3167000114917755},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.3018999993801117},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.2946999967098236},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.29429998993873596},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.2913999855518341},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26930001378059387},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.26910001039505005},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25119999051094055}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc58881.2025.11343651","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11343651","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4617446959018707,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W93957152","https://openalex.org/W1488890883","https://openalex.org/W1970242638","https://openalex.org/W1996610028","https://openalex.org/W2026292399","https://openalex.org/W2128495200","https://openalex.org/W2559463885","https://openalex.org/W2741907166","https://openalex.org/W2775675437","https://openalex.org/W2982470634","https://openalex.org/W3090156323","https://openalex.org/W3126287844","https://openalex.org/W3194020089","https://openalex.org/W4293451770","https://openalex.org/W4319970836","https://openalex.org/W4353094448","https://openalex.org/W4389274747","https://openalex.org/W4393359083","https://openalex.org/W4412521126"],"related_works":[],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,65,118,129],"learnable":[4,79],"frequency-weighting":[5,80],"layer":[6,81],"for":[7,68],"enhancing":[8,139],"EEG-based":[9,122,136],"Brain-Computer":[10],"Interface":[11],"(BCI)":[12],"performance,":[13],"particularly":[14],"in":[15,97,105,142],"higher-order":[16],"cognitive":[17,144],"tasks.":[18],"The":[19],"proposed":[20],"layer,":[21],"integrating":[22],"wavelet":[23],"transform":[24],"with":[25,37],"convolution":[26],"operations,":[27],"selectively":[28],"emphasizes":[29],"task-relevant":[30],"frequency":[31],"components":[32],"while":[33],"suppressing":[34],"those":[35],"associated":[36],"noise":[38],"or":[39],"unrelated":[40],"brain":[41],"activities.":[42],"We":[43],"evaluated":[44],"our":[45,101],"method":[46,116],"on":[47,53],"two":[48],"datasets\u2014a":[49],"local":[50],"dataset":[51,60],"focusing":[52],"spatial":[54],"perspective-taking":[55],"tasks":[56,106],"and":[57,91,131],"the":[58,62,78,112,115],"Cog-BCI":[59],"involving":[61],"N-back":[63],"task,":[64],"standard":[66],"paradigm":[67],"assessing":[69],"working":[70],"memory":[71],"load.":[72],"Empirical":[73],"results":[74],"indicate":[75],"that":[76],"incorporating":[77],"into":[82],"commonly":[83],"used":[84],"deep":[85],"learning":[86],"models":[87],"(EEGNet-V1,":[88],"EEGNet-V4,":[89],"ShallowConvNet,":[90],"DeepConvNet)":[92],"consistently":[93],"yields":[94],"significant":[95],"improvements":[96],"classification":[98],"accuracy.":[99],"Notably,":[100],"approach":[102,133],"demonstrates":[103],"effectiveness":[104],"exhibiting":[107],"similar":[108],"brain-wave":[109],"patterns,":[110],"underscoring":[111],"adaptability":[113],"of":[114,121],"to":[117,134],"wide":[119],"range":[120],"BCI":[123,137],"applications.":[124,145],"Overall,":[125],"this":[126],"study":[127],"provides":[128],"robust":[130],"generalizable":[132],"improving":[135],"systems,":[138],"their":[140],"practicality":[141],"real-world":[143]},"counts_by_year":[],"updated_date":"2026-02-23T20:09:44.859080","created_date":"2026-01-29T00:00:00"}
