{"id":"https://openalex.org/W2940831316","doi":"https://doi.org/10.1109/access.2019.2910191","title":"Recognition and Analysis of Motor Imagery EEG Signal Based on Improved BP Neural Network","display_name":"Recognition and Analysis of Motor Imagery EEG Signal Based on Improved BP Neural Network","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2940831316","doi":"https://doi.org/10.1109/access.2019.2910191","mag":"2940831316"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2910191","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2910191","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08685102.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08685102.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074043285","display_name":"Long Liu","orcid":"https://orcid.org/0000-0003-1762-3434"},"institutions":[{"id":"https://openalex.org/I4210117382","display_name":"Anyang Normal University","ror":"https://ror.org/02g9nss57","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210117382"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Long Liu","raw_affiliation_strings":["College of Physical Education, Anyang Normal University, Anyang, China"],"raw_orcid":"https://orcid.org/0000-0003-1762-3434","affiliations":[{"raw_affiliation_string":"College of Physical Education, Anyang Normal University, Anyang, China","institution_ids":["https://openalex.org/I4210117382"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5074043285"],"corresponding_institution_ids":["https://openalex.org/I4210117382"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":3.6135,"has_fulltext":true,"cited_by_count":41,"citation_normalized_percentile":{"value":0.93346155,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"7","issue":null,"first_page":"47794","last_page":"47803"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9541000127792358,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9440000057220459,"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/computer-science","display_name":"Computer science","score":0.7602417469024658},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6834582686424255},{"id":"https://openalex.org/keywords/motor-imagery","display_name":"Motor imagery","score":0.6439247131347656},{"id":"https://openalex.org/keywords/brain\u2013computer-interface","display_name":"Brain\u2013computer interface","score":0.585509717464447},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5568432211875916},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5174177885055542},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.501317024230957},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.4702405333518982},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4534892141819},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44677332043647766},{"id":"https://openalex.org/keywords/interface","display_name":"Interface (matter)","score":0.42819416522979736},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.41742897033691406},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.3770255744457245},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.325961709022522},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.2237531840801239},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.11280626058578491}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7602417469024658},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6834582686424255},{"id":"https://openalex.org/C54808283","wikidata":"https://www.wikidata.org/wiki/Q6918191","display_name":"Motor imagery","level":4,"score":0.6439247131347656},{"id":"https://openalex.org/C173201364","wikidata":"https://www.wikidata.org/wiki/Q897410","display_name":"Brain\u2013computer interface","level":3,"score":0.585509717464447},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5568432211875916},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5174177885055542},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.501317024230957},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.4702405333518982},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4534892141819},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44677332043647766},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.42819416522979736},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.41742897033691406},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.3770255744457245},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.325961709022522},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2237531840801239},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.11280626058578491},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0},{"id":"https://openalex.org/C157915830","wikidata":"https://www.wikidata.org/wiki/Q2928001","display_name":"Bubble","level":2,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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},{"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/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2910191","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2910191","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08685102.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:cef839c916f344059e00fd7dc894466b","is_oa":true,"landing_page_url":"https://doaj.org/article/cef839c916f344059e00fd7dc894466b","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 47794-47803 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2910191","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2910191","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08685102.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2940831316.pdf","grobid_xml":"https://content.openalex.org/works/W2940831316.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W1653844963","https://openalex.org/W2036469409","https://openalex.org/W2364089413","https://openalex.org/W2547868186","https://openalex.org/W2558378728","https://openalex.org/W2587633057","https://openalex.org/W2597004530","https://openalex.org/W2602110203","https://openalex.org/W2604870111","https://openalex.org/W2617586167","https://openalex.org/W2724572411","https://openalex.org/W2744185217","https://openalex.org/W2767333869","https://openalex.org/W2767388262","https://openalex.org/W2769399721","https://openalex.org/W2782128980","https://openalex.org/W2785124852","https://openalex.org/W2785761591","https://openalex.org/W2787792684","https://openalex.org/W2790727571","https://openalex.org/W2792655993","https://openalex.org/W2793381529","https://openalex.org/W2796045214","https://openalex.org/W2808945955","https://openalex.org/W2825158220","https://openalex.org/W2890397176"],"related_works":["https://openalex.org/W1977940006","https://openalex.org/W2887556756","https://openalex.org/W2947925238","https://openalex.org/W195417223","https://openalex.org/W2951110009","https://openalex.org/W1513407214","https://openalex.org/W1984377984","https://openalex.org/W1961545574","https://openalex.org/W2510077457","https://openalex.org/W3045772920"],"abstract_inverted_index":{"With":[0,28],"the":[1,10,29,35,61,67,70,83,93,100,133,145,155,161,166,174,180,189,193,199,203,232,241,248,267],"rapid":[2],"development":[3],"of":[4,12,31,38,60,69,80,95,165,192,205,235,258],"neuroinformatics":[5],"and":[6,14,23,26,33,42,54,104,111,124,171,210,256,276],"related":[7,36],"intelligent":[8,51],"algorithms,":[9,202],"research":[11,37,64],"recognition":[13,41,103,255,274],"classification":[15],"based":[16,131],"on":[17,132,198],"EEG":[18,39,75,102,214,261],"signals":[19],"is":[20,142],"becoming":[21],"more":[22,24],"important":[25,63],"valuable.":[27],"progress":[30],"science":[32],"technology,":[34],"signal":[40],"processing":[43,216],"has":[44,76,270],"been":[45],"gradually":[46],"applied":[47],"to":[48,144,153,187,231],"rehabilitation":[49],"medicine,":[50],"information":[52],"processing,":[53,115],"other":[55],"cross-cutting":[56],"fields.":[57],"As":[58],"one":[59],"most":[62],"directions":[65],"in":[66,92,113,213,222,254,273],"field":[68],"brain-computer":[71,236],"interface,":[72,237],"motor":[73,259],"imagery":[74,260],"a":[77,88],"wide":[78],"range":[79],"applications.":[81],"At":[82,98],"same":[84],"time,":[85],"it":[86],"shows":[87,265],"good":[89],"application":[90,96],"effect":[91],"process":[94],"practice.":[97],"present,":[99],"main":[101],"analysis":[105,257,277],"algorithms":[106],"always":[107],"have":[108],"some":[109],"problems":[110],"defects":[112],"data":[114,126,215,234],"such":[116],"as":[117,186],"low":[118,206],"signal-to-noise":[119,207],"ratio,":[120],"unclean":[121,211],"noise":[122],"filtering,":[123],"high":[125],"dimension.":[127],"In":[128,151],"this":[129,158,238],"paper,":[130],"improved":[134,242],"BP":[135,147,168,195,224,243,250],"neural":[136,148,169,244,251],"network":[137,149,245,252],"algorithm,":[138,184],"weight":[139,176,220],"splitting":[140],"technology":[141],"added":[143],"traditional":[146,167,223,249],"algorithm.":[150,196],"order":[152],"solve":[154],"filtering":[156,190,212],"problem,":[157],"paper":[159,239],"uses":[160],"non-linear":[162],"mapping":[163],"function":[164],"network,":[170],"intelligently":[172],"trains":[173],"small":[175],"particles":[177],"by":[178,218],"combining":[179],"particle":[181],"swarm":[182],"filter":[183],"so":[185],"improve":[188],"performance":[191],"whole":[194],"Based":[197],"above":[200],"two":[201],"problem":[204],"ratio":[208],"(SNR)":[209],"caused":[217],"fast":[219],"degradation":[221],"algorithm":[225,246,253,269],"can":[226],"be":[227],"solved.":[228],"Finally,":[229],"according":[230],"actual":[233],"compares":[240],"with":[247],"signals.":[262],"The":[263],"experiment":[264],"that":[266],"proposed":[268],"obvious":[271],"advantages":[272],"accuracy":[275],"effect.":[278]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":3},{"year":2014,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
