{"id":"https://openalex.org/W2973700007","doi":"https://doi.org/10.1109/access.2019.2941977","title":"Movements Classification of Multi-Channel sEMG Based on CNN and Stacking Ensemble Learning","display_name":"Movements Classification of Multi-Channel sEMG Based on CNN and Stacking Ensemble Learning","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2973700007","doi":"https://doi.org/10.1109/access.2019.2941977","mag":"2973700007"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2941977","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2941977","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08840853.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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/ielx7/6287639/8600701/08840853.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053923253","display_name":"Shu Shen","orcid":"https://orcid.org/0000-0003-3888-2427"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shu Shen","raw_affiliation_strings":["School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054023418","display_name":"Kang Gu","orcid":"https://orcid.org/0000-0001-8541-6205"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kang Gu","raw_affiliation_strings":["School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063203224","display_name":"Xinrong Chen","orcid":"https://orcid.org/0000-0002-4186-0678"},"institutions":[{"id":"https://openalex.org/I4210151021","display_name":"Shanghai Institute of Computing Technology","ror":"https://ror.org/05ek0ze18","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210151021"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin-Rong Chen","raw_affiliation_strings":["Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention, Shanghai, China","institution_ids":["https://openalex.org/I4210151021"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086247089","display_name":"Ming Yang","orcid":"https://orcid.org/0000-0002-6544-9226"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Yang","raw_affiliation_strings":["School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109232005","display_name":"Ruchuan Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ru-Chuan Wang","raw_affiliation_strings":["School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5053923253"],"corresponding_institution_ids":["https://openalex.org/I41198531"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":3.2722,"has_fulltext":true,"cited_by_count":67,"citation_normalized_percentile":{"value":0.92433386,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"7","issue":null,"first_page":"137489","last_page":"137500"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9991000294685364,"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/T10914","display_name":"Tactile and Sensory Interactions","score":0.9868999719619751,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7511785626411438},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7383596897125244},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7264813184738159},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7102749347686768},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5980109572410583},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.594157874584198},{"id":"https://openalex.org/keywords/sliding-window-protocol","display_name":"Sliding window protocol","score":0.4433443546295166},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3325819671154022},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.12719550728797913}],"concepts":[{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7511785626411438},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7383596897125244},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7264813184738159},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7102749347686768},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5980109572410583},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.594157874584198},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.4433443546295166},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3325819671154022},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.12719550728797913},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2941977","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2941977","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08840853.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:a6aeca0dbf6c4701a055da658bfd787a","is_oa":true,"landing_page_url":"https://doaj.org/article/a6aeca0dbf6c4701a055da658bfd787a","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 137489-137500 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2941977","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2941977","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08840853.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.44999998807907104},{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.44999998807907104}],"awards":[{"id":"https://openalex.org/G1023919524","display_name":null,"funder_award_id":", Grant","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1557924762","display_name":null,"funder_award_id":"TITAN X","funder_id":"https://openalex.org/F4320309480","funder_display_name":"Nvidia"},{"id":"https://openalex.org/G2082826544","display_name":null,"funder_award_id":"Postdoctoral","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2891540903","display_name":null,"funder_award_id":"61572261","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3290416353","display_name":null,"funder_award_id":"61701168","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3464246607","display_name":null,"funder_award_id":"61572261","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4020255992","display_name":null,"funder_award_id":"Project","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4582478976","display_name":null,"funder_award_id":"61572260","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G5009802290","display_name":null,"funder_award_id":"61401221","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5848258319","display_name":null,"funder_award_id":"0 and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7345446748","display_name":"Middle and Upper Devonian Black Shales: Testing the Productivity-Anoxia Feedback and Land Plant-Weathering Rate Hypotheses","funder_award_id":"0618003","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7465113774","display_name":null,"funder_award_id":"61873131","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8260748776","display_name":null,"funder_award_id":"2016M601860","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8661684169","display_name":null,"funder_award_id":"61572260","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G88198729","display_name":null,"funder_award_id":"61872196","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320321605","display_name":"Government of Jiangsu Province","ror":"https://ror.org/004svx814"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2973700007.pdf","grobid_xml":"https://content.openalex.org/works/W2973700007.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2037967616","https://openalex.org/W2082480549","https://openalex.org/W2123167643","https://openalex.org/W2129566274","https://openalex.org/W2165619603","https://openalex.org/W2169931829","https://openalex.org/W2516710120","https://openalex.org/W2588906820","https://openalex.org/W2684229413","https://openalex.org/W2752782242","https://openalex.org/W2762706434","https://openalex.org/W2781714299","https://openalex.org/W2793187201","https://openalex.org/W2793560507","https://openalex.org/W2884201223","https://openalex.org/W2898716605","https://openalex.org/W2898980383","https://openalex.org/W2899020521","https://openalex.org/W2911956695","https://openalex.org/W2923078152","https://openalex.org/W2962685937","https://openalex.org/W4240294902","https://openalex.org/W6631190155","https://openalex.org/W6697462184","https://openalex.org/W6733981828","https://openalex.org/W6749556538"],"related_works":["https://openalex.org/W2353818951","https://openalex.org/W4293226380","https://openalex.org/W1605879311","https://openalex.org/W2611980620","https://openalex.org/W2385763735","https://openalex.org/W2386394344","https://openalex.org/W2382806131","https://openalex.org/W2006683254","https://openalex.org/W4400976415","https://openalex.org/W2770255720"],"abstract_inverted_index":{"In":[0,74],"recent":[1],"years,":[2],"the":[3,35,44,102,123,138,142,154,160,177,196,205,210,216,228,233,239,251,274,277,281,297],"analysis":[4,48],"of":[5,28,46,60,93,122,191,198,202,231,280],"surface":[6],"electromyography":[7],"(sEMG)":[8],"signals":[9,36],"by":[10,159,188],"feature":[11,21,26,32,95],"engineering":[12,22],"and":[13,49,70,118,151,163,176,181,193,215,224,238,247,270,287,293,306],"machine":[14],"learning":[15],"has":[16],"developed":[17],"rapidly.":[18],"However,":[19],"when":[20],"is":[23,83,105,134,145,149,208,254,284,301],"applied":[24],"to":[25,57,85,107,136],"extraction":[27],"sEMG":[29,61,87,124,155,184],"signals,":[30],"important":[31,94],"information":[33],"in":[34,195],"will":[37,42],"inevitably":[38],"be":[39,222],"omitted,":[40],"which":[41,90],"reduce":[43],"performance":[45],"signal":[47,125,156,185],"recognition.":[50],"Therefore,":[51],"this":[52,75],"paper":[53],"proposes":[54],"a":[55,77,199],"method":[56,104],"complete":[58],"classification":[59],"hand":[62],"movements":[63],"based":[64,80,100],"on":[65,81,101,130],"convolutional":[66],"neural":[67],"network":[68],"(CNN)":[69],"stacking":[71,103],"ensemble":[72],"learning.":[73],"method,":[76],"primary":[78,110,147,174,212,235],"classifier":[79,99,148,175,179,213,219,236,242,283],"CNN":[82],"designed":[84,106,253],"extract":[86],"data":[88,121,157,186],"features,":[89],"avoid":[91],"omission":[92],"information.":[96],"A":[97],"secondary":[98,178,218,241,282],"integrate":[108],"three":[109],"classifiers":[111],"trained":[112,150,180],"with":[113,153,183,256],"time":[114],"domain,":[115],"frequency":[116],"domain":[117,120],"time-frequency":[119],"respectively.":[126,226,249,295],"Then,":[127],"several":[128],"experiments":[129],"NinaPro":[131],"DB5":[132],"dataset":[133],"performed":[135],"evaluate":[137],"proposed":[139],"models.":[140],"When":[141,204],"window":[143,189,206,229],"length":[144,201,207,230],"200ms,":[146,209],"tested":[152,182],"divided":[158,187],"80ms,":[161],"100ms,":[162],"125ms":[164],"sliding":[165,200],"length.":[166],"The":[167,173],"best":[168,211,217,234,240],"accuracy":[169,214,220,237,243,279,299],"can":[170,221,244],"reach":[171,245],"71%.":[172],"lengths":[190],"200ms":[192],"300ms":[194],"case":[197],"100ms.":[203],"70.92%":[223],"72.09%,":[225],"On":[227],"300ms,":[232],"75.02%":[246],"76.02%,":[248],"Finally,":[250],"model":[252],"compared":[255],"Linear":[257],"Discriminant":[258],"Analysis":[259],"(LDA),":[260],"Long":[261],"Short":[262],"Term":[263],"Memory-CNN":[264],"(LCNN),":[265],"Support":[266],"Vector":[267],"Machine":[268],"(SVM),":[269],"Random":[271,307],"Forests.":[272,308],"Under":[273],"same":[275],"conditions,":[276],"average":[278,298],"11.5%,":[285],"13.6%.":[286],"10.1%":[288],"higher":[289,303],"than":[290,304],"LDA,":[291],"SVM,":[292],"LCNN,":[294],"Also,":[296],"rate":[300],"3.05%":[302],"SVM":[305]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":21},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":5}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}