{"id":"https://openalex.org/W1532531499","doi":"https://doi.org/10.1109/ascc.2015.7244386","title":"ICA-based positive semidefinite matrix templates for eye-blink artifact removal from EEG signal with single-electrode","display_name":"ICA-based positive semidefinite matrix templates for eye-blink artifact removal from EEG signal with single-electrode","publication_year":2015,"publication_date":"2015-05-01","ids":{"openalex":"https://openalex.org/W1532531499","doi":"https://doi.org/10.1109/ascc.2015.7244386","mag":"1532531499"},"language":"en","primary_location":{"id":"doi:10.1109/ascc.2015.7244386","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ascc.2015.7244386","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 10th Asian Control Conference (ASCC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5025266672","display_name":"Suguru Kanoga","orcid":"https://orcid.org/0000-0002-2214-3622"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Suguru Kanoga","raw_affiliation_strings":["Graduate School of Science and Technology, Keio University, Kanagawa, Japan","Graduate School of Science and Technology, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama, Kanagawa, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Technology, Keio University, Kanagawa, Japan","institution_ids":["https://openalex.org/I203951103"]},{"raw_affiliation_string":"Graduate School of Science and Technology, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama, Kanagawa, Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020657583","display_name":"Yasue Mitsukura","orcid":"https://orcid.org/0000-0001-5575-8589"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yasue Mitsukura","raw_affiliation_strings":["Faculty of Science and Technology, Keio University, Kanagawa, Japan","Faculty of Science and Technology; Keio University; 3-14-1 Hiyoshi Kohoku-ku Yokohama, Kanagawa Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Science and Technology, Keio University, Kanagawa, Japan","institution_ids":["https://openalex.org/I203951103"]},{"raw_affiliation_string":"Faculty of Science and Technology; Keio University; 3-14-1 Hiyoshi Kohoku-ku Yokohama, Kanagawa Japan","institution_ids":["https://openalex.org/I203951103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I203951103"],"apc_list":null,"apc_paid":null,"fwci":0.2428,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.36170213,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"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/T11447","display_name":"Blind Source Separation Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.991100013256073,"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/T10860","display_name":"Speech and Audio Processing","score":0.9846000075340271,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/artifact","display_name":"Artifact (error)","score":0.8036003112792969},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6766864657402039},{"id":"https://openalex.org/keywords/independent-component-analysis","display_name":"Independent component analysis","score":0.630907416343689},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5716572999954224},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.5611215829849243},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5348431468009949},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.46608608961105347},{"id":"https://openalex.org/keywords/blind-signal-separation","display_name":"Blind signal separation","score":0.45371800661087036},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4353833496570587},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41764557361602783},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4164593815803528},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.38701096177101135},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.10824418067932129},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.061567217111587524}],"concepts":[{"id":"https://openalex.org/C2779010991","wikidata":"https://www.wikidata.org/wiki/Q2720909","display_name":"Artifact (error)","level":2,"score":0.8036003112792969},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6766864657402039},{"id":"https://openalex.org/C51432778","wikidata":"https://www.wikidata.org/wiki/Q1259145","display_name":"Independent component analysis","level":2,"score":0.630907416343689},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5716572999954224},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.5611215829849243},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5348431468009949},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.46608608961105347},{"id":"https://openalex.org/C120317606","wikidata":"https://www.wikidata.org/wiki/Q17105967","display_name":"Blind signal separation","level":3,"score":0.45371800661087036},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4353833496570587},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41764557361602783},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4164593815803528},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.38701096177101135},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.10824418067932129},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.061567217111587524},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ascc.2015.7244386","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ascc.2015.7244386","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 10th Asian Control Conference (ASCC)","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":30,"referenced_works":["https://openalex.org/W41179353","https://openalex.org/W1504438288","https://openalex.org/W1548915175","https://openalex.org/W1902027874","https://openalex.org/W1971913428","https://openalex.org/W1989793585","https://openalex.org/W1992239553","https://openalex.org/W2001298302","https://openalex.org/W2001834784","https://openalex.org/W2028058536","https://openalex.org/W2033468335","https://openalex.org/W2035480992","https://openalex.org/W2051663518","https://openalex.org/W2079277602","https://openalex.org/W2080851732","https://openalex.org/W2081144582","https://openalex.org/W2090418688","https://openalex.org/W2097939965","https://openalex.org/W2107012213","https://openalex.org/W2108384452","https://openalex.org/W2137359389","https://openalex.org/W2157765880","https://openalex.org/W2164360360","https://openalex.org/W2169064120","https://openalex.org/W2173416859","https://openalex.org/W4232944527","https://openalex.org/W6601726404","https://openalex.org/W6674525294","https://openalex.org/W6683344597","https://openalex.org/W6684585955"],"related_works":["https://openalex.org/W2390344110","https://openalex.org/W2364896863","https://openalex.org/W2361066326","https://openalex.org/W2046761971","https://openalex.org/W2182042810","https://openalex.org/W2156932837","https://openalex.org/W2380698615","https://openalex.org/W374502268","https://openalex.org/W2103029460","https://openalex.org/W1785857632"],"abstract_inverted_index":{"Complete":[0],"artifact":[1,23,43,106,124],"removal":[2,24,44,107,125],"of":[3,21,88,122,129],"eye-blink":[4,22,42,105,123],"for":[5,25,46,109],"electroencephalographic":[6],"(EEG)":[7],"signal":[8,16,28,49,112],"is":[9,32,96],"generally-regarded":[10],"as":[11],"important":[12],"process":[13],"in":[14,29,65,94],"EEG":[15,27,48,111],"analysis.":[17],"No":[18],"numerical":[19],"approach":[20],"single-channel":[26,47,110],"time":[30,40,103],"domain":[31,41,104],"developed.":[33],"In":[34],"this":[35],"paper,":[36],"we":[37,72],"propose":[38],"a":[39,70],"method":[45,108],"using":[50,116],"independent":[51],"component":[52],"analysis":[53],"(ICA)-based":[54],"templates.":[55,120],"ICA":[56],"and":[57,78,127],"positive":[58],"semidefinite":[59],"tensor":[60],"factorization":[61],"(PSDTF)":[62],"are":[63,132],"employed":[64],"our":[66,133],"proposed":[67,114],"method.":[68],"As":[69],"result,":[71],"obtain":[73],"high":[74],"signal-to-noise":[75],"ratio":[76],"(15.03dB)":[77],"low":[79],"mean":[80],"square":[81],"error":[82],"(25.76).":[83],"Moreover,":[84],"the":[85],"optimal":[86],"number":[87],"iterations":[89],"on":[90],"multiplicative":[91],"update":[92],"rules":[93],"PSDTF":[95],"about":[97],"20":[98],"to":[99],"30.":[100],"A":[101],"useful":[102],"was":[113],"by":[115],"ICA-based":[117],"PSD":[118],"matrix":[119],"Improvement":[121],"accuracy":[126],"reduction":[128],"computational":[130],"cost":[131],"main":[134],"future":[135],"works.":[136]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
