{"id":"https://openalex.org/W3172919124","doi":"https://doi.org/10.1109/ner49283.2021.9441307","title":"Hybrid Template Canonical Correlation Analysis Method for Enhancing SSVEP Recognition under data-limited Condition","display_name":"Hybrid Template Canonical Correlation Analysis Method for Enhancing SSVEP Recognition under data-limited Condition","publication_year":2021,"publication_date":"2021-05-04","ids":{"openalex":"https://openalex.org/W3172919124","doi":"https://doi.org/10.1109/ner49283.2021.9441307","mag":"3172919124"},"language":"en","primary_location":{"id":"doi:10.1109/ner49283.2021.9441307","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ner49283.2021.9441307","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 10th International IEEE/EMBS Conference on Neural Engineering (NER)","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/A5030774974","display_name":"Runfeng Miao","orcid":null},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Runfeng Miao","raw_affiliation_strings":["Chongqing University - University of Cincinnati Joint Co-op Insitute, China","Chongqing University - University of Cincinnati Joint Co-op Insitute,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University - University of Cincinnati Joint Co-op Insitute, China","institution_ids":["https://openalex.org/I158842170"]},{"raw_affiliation_string":"Chongqing University - University of Cincinnati Joint Co-op Insitute,China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100425432","display_name":"Li Zhang","orcid":"https://orcid.org/0000-0001-7294-9395"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Zhang","raw_affiliation_strings":["State Key Laboratory of Power Transmission Equipment & System Security and New Technology, School of Electrical Engineering, Chongqing University, China","State Key Laboratory of Power Transmission Equipment & System Security and New Technology, School of Electrical Engineering, Chongqing University,Electrical Engineering Department,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Power Transmission Equipment & System Security and New Technology, School of Electrical Engineering, Chongqing University, China","institution_ids":["https://openalex.org/I158842170"]},{"raw_affiliation_string":"State Key Laboratory of Power Transmission Equipment & System Security and New Technology, School of Electrical Engineering, Chongqing University,Electrical Engineering Department,China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102949726","display_name":"Qiang Sun","orcid":"https://orcid.org/0000-0002-1125-4706"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Sun","raw_affiliation_strings":["State Key Laboratory of Power Transmission Equipment & System Security and New Technology, School of Electrical Engineering, Chongqing University, China","[State Key Laboratory of Power Transmission Equipment & System Security and New Technology School of Electrical Engineering, Chongqing University, China]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Power Transmission Equipment & System Security and New Technology, School of Electrical Engineering, Chongqing University, China","institution_ids":["https://openalex.org/I158842170"]},{"raw_affiliation_string":"[State Key Laboratory of Power Transmission Equipment & System Security and New Technology School of Electrical Engineering, Chongqing University, China]","institution_ids":["https://openalex.org/I158842170"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I158842170"],"apc_list":null,"apc_paid":null,"fwci":1.2467,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.75499811,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"65","last_page":"68"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9998999834060669,"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":0.9998999834060669,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9958999752998352,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9958999752998352,"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/canonical-correlation","display_name":"Canonical correlation","score":0.9091246724128723},{"id":"https://openalex.org/keywords/brain\u2013computer-interface","display_name":"Brain\u2013computer interface","score":0.819736123085022},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8101028800010681},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6242208480834961},{"id":"https://openalex.org/keywords/interface","display_name":"Interface (matter)","score":0.597142219543457},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5478508472442627},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5169424414634705},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49796509742736816},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4937659204006195},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.4746549725532532},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4542534649372101},{"id":"https://openalex.org/keywords/template","display_name":"Template","score":0.4116584062576294},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36921489238739014},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0890055000782013}],"concepts":[{"id":"https://openalex.org/C153874254","wikidata":"https://www.wikidata.org/wiki/Q115542","display_name":"Canonical correlation","level":2,"score":0.9091246724128723},{"id":"https://openalex.org/C173201364","wikidata":"https://www.wikidata.org/wiki/Q897410","display_name":"Brain\u2013computer interface","level":3,"score":0.819736123085022},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8101028800010681},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6242208480834961},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.597142219543457},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5478508472442627},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5169424414634705},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49796509742736816},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4937659204006195},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.4746549725532532},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4542534649372101},{"id":"https://openalex.org/C82714645","wikidata":"https://www.wikidata.org/wiki/Q438331","display_name":"Template","level":2,"score":0.4116584062576294},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36921489238739014},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0890055000782013},{"id":"https://openalex.org/C157915830","wikidata":"https://www.wikidata.org/wiki/Q2928001","display_name":"Bubble","level":2,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"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/C129307140","wikidata":"https://www.wikidata.org/wiki/Q6795880","display_name":"Maximum bubble pressure method","level":3,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ner49283.2021.9441307","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ner49283.2021.9441307","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 10th International IEEE/EMBS Conference on Neural Engineering (NER)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7084822490","display_name":null,"funder_award_id":"51977020","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1994855515","https://openalex.org/W2060004431","https://openalex.org/W2154366912","https://openalex.org/W2163939660","https://openalex.org/W2338492816","https://openalex.org/W2553904372","https://openalex.org/W2605492512","https://openalex.org/W3007062513","https://openalex.org/W3008442772","https://openalex.org/W3080484934"],"related_works":["https://openalex.org/W2321737855","https://openalex.org/W2293800410","https://openalex.org/W1991496323","https://openalex.org/W3183638985","https://openalex.org/W4320021951","https://openalex.org/W2216848651","https://openalex.org/W2367413540","https://openalex.org/W1968846550","https://openalex.org/W2236178445","https://openalex.org/W1991315556"],"abstract_inverted_index":{"In":[0],"this":[1],"study,":[2],"an":[3],"advanced":[4],"CCA-based":[5],"algorithm":[6],"called":[7],"hybrid":[8],"template":[9],"canonical":[10],"correlation":[11],"analysis":[12],"(HTCCA)":[13],"was":[14],"proposed":[15,61,114],"to":[16,45,100],"improve":[17],"the":[18,39,60,64,76,113,120],"performance":[19],"of":[20,78,122],"brain-computer":[21,124],"interface":[22],"(BCI)":[23],"based":[24,104],"on":[25,53,105],"steady":[26],"state":[27],"visual":[28],"evoked":[29],"potential":[30,118],"(SSVEP)":[31],"under":[32],"data-limited":[33],"condition.":[34],"The":[35,49],"HTCCA":[36],"method":[37,62,115],"combines":[38],"training":[40],"data":[41],"from":[42],"several":[43],"subjects":[44],"construct":[46],"SSVEP":[47],"templates.":[48],"experimental":[50],"results":[51],"evaluated":[52],"two":[54],"public":[55],"benchmark":[56],"datasets":[57],"showed":[58],"that":[59,83,112],"outperforms":[63],"compared":[65],"methods":[66,103],"in":[67,93,119],"both":[68],"detection":[69],"accuracy":[70],"and":[71],"information":[72],"transfer":[73],"rate":[74],"when":[75],"number":[77],"trials":[79],"is":[80,97],"small.":[81],"Considering":[82],"user-friendly":[84],"experience":[85],"will":[86],"become":[87],"a":[88],"key":[89],"factor":[90],"for":[91],"BCI":[92],"practical":[94],"application,":[95],"it":[96],"very":[98],"necessary":[99],"develop":[101],"effective":[102],"limited":[106],"EEG":[107],"samples.":[108],"This":[109],"study":[110],"demonstrates":[111],"has":[116],"great":[117],"application":[121],"SSVEP-based":[123],"interfaces.":[125]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}