{"id":"https://openalex.org/W3018758218","doi":"https://doi.org/10.1109/civemsa45640.2019.9071624","title":"Motor imagery signal classification based on transfer learning","display_name":"Motor imagery signal classification based on transfer learning","publication_year":2019,"publication_date":"2019-06-01","ids":{"openalex":"https://openalex.org/W3018758218","doi":"https://doi.org/10.1109/civemsa45640.2019.9071624","mag":"3018758218"},"language":"en","primary_location":{"id":"doi:10.1109/civemsa45640.2019.9071624","is_oa":false,"landing_page_url":"https://doi.org/10.1109/civemsa45640.2019.9071624","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","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/A5101691668","display_name":"Banghua Yang","orcid":"https://orcid.org/0000-0002-8561-5631"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Banghua Yang","raw_affiliation_strings":["School of Mechatronic Engineering and Automation, Research Center of Brain Computer Engineering, Shanghai University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Mechatronic Engineering and Automation, Research Center of Brain Computer Engineering, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085926568","display_name":"Minmin Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I64449678","display_name":"Putian University","ror":"https://ror.org/00jmsxk74","country_code":"CN","type":"education","lineage":["https://openalex.org/I64449678"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minmin Zheng","raw_affiliation_strings":["School of Mechanical and Electrical Engineering, Putian University, Fujian, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical and Electrical Engineering, Putian University, Fujian, China","institution_ids":["https://openalex.org/I64449678"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031778999","display_name":"Cuntai Guan","orcid":"https://orcid.org/0000-0002-0872-3276"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Guan Cuntai","raw_affiliation_strings":["School of Computer Science and Engineering, Nanyang Technological University, Nanyang, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanyang Technological University, Nanyang, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046508099","display_name":"Bo Li","orcid":"https://orcid.org/0000-0002-1415-4444"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Bo","raw_affiliation_strings":["School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101691668"],"corresponding_institution_ids":["https://openalex.org/I113940042"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.21636998,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"22","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":0.9998000264167786,"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":0.9998000264167786,"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":0.9832000136375427,"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"}},{"id":"https://openalex.org/T11601","display_name":"Neuroscience and Neural Engineering","score":0.9635999798774719,"subfield":{"id":"https://openalex.org/subfields/2804","display_name":"Cellular and Molecular Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/motor-imagery","display_name":"Motor imagery","score":0.7543299198150635},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6788652539253235},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.6609417200088501},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6549572348594666},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5805262327194214},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5650601387023926},{"id":"https://openalex.org/keywords/brain\u2013computer-interface","display_name":"Brain\u2013computer interface","score":0.5079987645149231},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4498422145843506},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3735977113246918},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.3480032980442047}],"concepts":[{"id":"https://openalex.org/C54808283","wikidata":"https://www.wikidata.org/wiki/Q6918191","display_name":"Motor imagery","level":4,"score":0.7543299198150635},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6788652539253235},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.6609417200088501},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6549572348594666},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5805262327194214},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5650601387023926},{"id":"https://openalex.org/C173201364","wikidata":"https://www.wikidata.org/wiki/Q897410","display_name":"Brain\u2013computer interface","level":3,"score":0.5079987645149231},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4498422145843506},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3735977113246918},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.3480032980442047},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/civemsa45640.2019.9071624","is_oa":false,"landing_page_url":"https://doi.org/10.1109/civemsa45640.2019.9071624","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","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":12,"referenced_works":["https://openalex.org/W990114106","https://openalex.org/W1509205144","https://openalex.org/W1995059973","https://openalex.org/W2093792557","https://openalex.org/W2110863214","https://openalex.org/W2131321253","https://openalex.org/W2145302786","https://openalex.org/W2152119085","https://openalex.org/W2252818737","https://openalex.org/W2254990556","https://openalex.org/W2792687613","https://openalex.org/W3124617164"],"related_works":["https://openalex.org/W1977940006","https://openalex.org/W2887556756","https://openalex.org/W2947925238","https://openalex.org/W195417223","https://openalex.org/W1513407214","https://openalex.org/W1984377984","https://openalex.org/W1961545574","https://openalex.org/W2510077457","https://openalex.org/W3045772920","https://openalex.org/W2047816336"],"abstract_inverted_index":{"The":[0],"EEG":[1],"of":[2,30,38,51,119,170,180,190],"motor":[3,125,133,194],"imagery":[4,126,134,195],"varies":[5],"greatly":[6],"according":[7],"to":[8,75,86,98,124],"different":[9,16],"subjects":[10],"and":[11,28,40,43,63,80,108,131,138,157,183,198],"the":[12,26,31,41,49,77,89,93,100,115,132,147,162,167,188],"same":[13,32],"subject":[14],"in":[15,83,92,193],"time":[17],"periods.":[18],"Traditional":[19],"machine":[20],"learning":[21,68,78,90,102,107,110,142,172,192],"methods":[22,60,152],"can":[23,69],"only":[24],"solve":[25],"classification":[27,42,59,151,168,197],"recognition":[29,44],"individual":[33,56],"within":[34],"a":[35],"short":[36],"period":[37],"time,":[39],"effect":[45],"also":[46],"depends":[47],"on":[48],"difference":[50],"data":[52,74,135],"sets,":[53],"with":[54,146],"strong":[55],"differences.":[57],"Many":[58],"are":[61],"unstable":[62],"have":[64],"poor":[65],"universality.":[66],"Transfer":[67],"use":[70,81],"knowledge":[71,82],"from":[72,103],"similar":[73],"enhance":[76],"process,":[79],"related":[84,123],"fields":[85],"help":[87],"complete":[88],"tasks":[91],"target":[94],"field,":[95],"so":[96],"as":[97],"change":[99],"traditional":[101,181],"scratch":[104],"into":[105],"accumulated":[106],"improve":[109],"efficiency.":[111],"In":[112],"this":[113],"paper,":[114],"power":[116],"spectrum":[117],"characteristics":[118],"8":[120],"channels":[121],"signals":[122],"at":[127],"7-29hz":[128],"were":[129,136],"extracted,":[130],"classified":[137],"modeled":[139],"by":[140],"transfer":[141,171,191],"algorithm.":[143],"Meanwhile,":[144],"compared":[145],"other":[148],"two":[149],"existing":[150],"PSD":[153],"(Power":[154],"Spectral":[155],"Density)":[156],"CSP":[158],"(Common":[159],"Spatial":[160],"Pattern),":[161],"analysis":[163],"results":[164],"showed":[165],"that":[166,179],"accuracy":[169],"(90.9":[173],"\u00b1":[174],"2.2)":[175],"was":[176],"higher":[177],"than":[178],"PSD+LDA(62.5\u00b111.6)":[182],"CSP+SVM":[184],"(71.3\u00b13.5),":[185],"which":[186],"verified":[187],"feasibility":[189],"BCI":[196],"recognition.":[199]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
