{"id":"https://openalex.org/W4382119223","doi":"https://doi.org/10.1109/tim.2023.3289556","title":"Research on Multimodal Fusion Recognition Method of Upper Limb Motion Patterns","display_name":"Research on Multimodal Fusion Recognition Method of Upper Limb Motion Patterns","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4382119223","doi":"https://doi.org/10.1109/tim.2023.3289556"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2023.3289556","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3289556","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Instrumentation and Measurement","raw_type":"journal-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/A5100329066","display_name":"Wendong Wang","orcid":"https://orcid.org/0000-0002-2336-0477"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wendong Wang","raw_affiliation_strings":["Department of Industrial Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-2336-0477","affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081910136","display_name":"Chengzhi Zhao","orcid":"https://orcid.org/0000-0001-5286-9419"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengzhi Zhao","raw_affiliation_strings":["Department of Industrial Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0001-5286-9419","affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xin Li","orcid":"https://orcid.org/0000-0002-0289-6926"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Li","raw_affiliation_strings":["Department of Industrial Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-0289-6926","affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050079548","display_name":"Zhiqiang Zhang","orcid":"https://orcid.org/0000-0003-0204-3867"},"institutions":[{"id":"https://openalex.org/I130828816","display_name":"University of Leeds","ror":"https://ror.org/024mrxd33","country_code":"GB","type":"education","lineage":["https://openalex.org/I130828816"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Zhi-Qiang Zhang","raw_affiliation_strings":["Institute of Robotics, Autonomous System and Sensing, School of Electrical and Electronic Engineering, University of Leeds, Leeds, U.K"],"raw_orcid":"https://orcid.org/0000-0003-0204-3867","affiliations":[{"raw_affiliation_string":"Institute of Robotics, Autonomous System and Sensing, School of Electrical and Electronic Engineering, University of Leeds, Leeds, U.K","institution_ids":["https://openalex.org/I130828816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100610020","display_name":"Xiaoqing Yuan","orcid":"https://orcid.org/0000-0002-0672-6895"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoqing Yuan","raw_affiliation_strings":["Department of Industrial Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-0672-6895","affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101614299","display_name":"Hanhao Li","orcid":"https://orcid.org/0000-0002-0315-270X"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanhao Li","raw_affiliation_strings":["Department of Industrial Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-0315-270X","affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100329066"],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":9.8652,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.98073599,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"72","issue":null,"first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13647","display_name":"AI and Big Data Applications","score":0.9459999799728394,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T13647","display_name":"AI and Big Data Applications","score":0.9459999799728394,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7597149610519409},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6186537742614746},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6146318912506104},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.5595105290412903},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5464178919792175},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4871692359447479},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.13242432475090027}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7597149610519409},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6186537742614746},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6146318912506104},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.5595105290412903},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5464178919792175},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4871692359447479},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.13242432475090027}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tim.2023.3289556","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3289556","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Instrumentation and Measurement","raw_type":"journal-article"},{"id":"pmh:oai:eprints.whiterose.ac.uk:201489","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306400854","display_name":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2800616092","host_organization_name":"White Rose University Consortium","host_organization_lineage":["https://openalex.org/I2800616092"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G144635991","display_name":null,"funder_award_id":"2020JM-131","funder_id":"https://openalex.org/F4320324173","funder_display_name":"Natural Science Foundation of Shaanxi Province"},{"id":"https://openalex.org/G3899699280","display_name":null,"funder_award_id":"2020KW-058","funder_id":"https://openalex.org/F4320324173","funder_display_name":"Natural Science Foundation of Shaanxi Province"}],"funders":[{"id":"https://openalex.org/F4320324173","display_name":"Natural Science Foundation of Shaanxi Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1991274249","https://openalex.org/W2018015124","https://openalex.org/W2027717478","https://openalex.org/W2028880308","https://openalex.org/W2044628302","https://openalex.org/W2101713460","https://openalex.org/W2151840867","https://openalex.org/W2243789297","https://openalex.org/W2330589301","https://openalex.org/W2738029666","https://openalex.org/W2756980343","https://openalex.org/W2761040405","https://openalex.org/W2888491225","https://openalex.org/W2892335058","https://openalex.org/W2909970681","https://openalex.org/W2912787333","https://openalex.org/W2922442184","https://openalex.org/W2949402129","https://openalex.org/W2962879438","https://openalex.org/W2963163009","https://openalex.org/W2963172626","https://openalex.org/W2997304337","https://openalex.org/W3012303644","https://openalex.org/W3021157419","https://openalex.org/W3046341008","https://openalex.org/W3071682211","https://openalex.org/W3080919303","https://openalex.org/W3092843091","https://openalex.org/W3093217586","https://openalex.org/W3109996502","https://openalex.org/W3170603112","https://openalex.org/W3188452244","https://openalex.org/W4200234541","https://openalex.org/W4205449877","https://openalex.org/W4206217267","https://openalex.org/W4236325002","https://openalex.org/W4281636610","https://openalex.org/W4288062164","https://openalex.org/W4297828517","https://openalex.org/W6675357634","https://openalex.org/W6741502269"],"related_works":["https://openalex.org/W2755342338","https://openalex.org/W2058170566","https://openalex.org/W2036807459","https://openalex.org/W2775347418","https://openalex.org/W1969923398","https://openalex.org/W2166024367","https://openalex.org/W2772917594","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2079911747"],"abstract_inverted_index":{"In":[0],"order":[1],"to":[2,151,176],"solve":[3],"the":[4,49,56,64,82,90,96,108,113,121,124,159,167,177,185,194,208],"problems":[5],"of":[6,16,51,75,84,95,123,142,158,166,199,210],"single":[7],"movement":[8],"pattern":[9,44,116,145],"recognition":[10,14,45,117,140,190,203],"information":[11,25,188],"and":[12,32,36,89,112,130,196,205],"low":[13],"accuracy":[15,141,195],"multi-joint":[17],"upper":[18,41,200,211],"limb":[19,42,201,212],"exoskeleton":[20],"rehabilitation":[21,213],"training,":[22],"a":[23,70],"multimodal":[24,52,187],"fusion":[26,189],"method":[27,191],"with":[28],"human":[29,114],"surface":[30],"electromyography(sEMG)":[31],"electrocardiogram(ECG)":[33],"was":[34,46,67,99,104,118],"proposed,":[35],"an":[37],"Inception-Sim":[38,102,169],"model":[39,103,170],"for":[40,146],"motion":[43,115,144,202],"designed.":[47],"Integrating":[48],"advantages":[50],"information,":[53],"inspired":[54],"by":[55,172],"convolutional":[57],"neural":[58],"network":[59],"processing":[60],"image":[61,79,98],"classification":[62],"problem,":[63],"original":[65],"signal":[66],"converted":[68],"into":[69],"Gramian":[71],"Angular":[72],"Summation/Difference":[73],"Fields-Histogram":[74],"Oriented":[76],"Gradient":[77],"(GASF/GADF-HOG)":[78],"based":[80,106],"on":[81,107,120],"principle":[83],"Grameen":[85],"angle":[86],"superposition/difference":[87],"field,":[88],"directional":[91],"gradient":[92],"histogram":[93],"feature":[94],"GASF/GADF":[97],"extracted.":[100],"The":[101,139,162,180],"constructed":[105],"Inception":[109],"V3":[110],"model,":[111],"completed":[119],"basis":[122],"transfer":[125],"learning":[126],"network.":[127],"VGG16,":[128],"ResNet-50,":[129],"other":[131],"backbone":[132],"networks":[133],"were":[134],"selected":[135],"as":[136],"comparison":[137],"models.":[138],"each":[143],"all":[147],"participants":[148],"reaches":[149],"up":[150],"90%,":[152],"which":[153],"is":[154],"better":[155],"than":[156],"that":[157,184],"control":[160,178],"model.":[161,179],"average":[163],"iteration":[164,197],"speed":[165,198],"proposed":[168,186],"improved":[171],"about":[173],"21%":[174],"compared":[175],"experimental":[181],"results":[182],"show":[183],"can":[192],"improve":[193,207],"mode":[204],"then":[206],"effect":[209],"training.":[214]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}