{"id":"https://openalex.org/W4393371251","doi":"https://doi.org/10.1016/j.bspc.2024.106261","title":"Comparison of fine-tuned single-source and multi-source approaches to surface electromyogram pattern recognition","display_name":"Comparison of fine-tuned single-source and multi-source approaches to surface electromyogram pattern recognition","publication_year":2024,"publication_date":"2024-04-01","ids":{"openalex":"https://openalex.org/W4393371251","doi":"https://doi.org/10.1016/j.bspc.2024.106261"},"language":"en","primary_location":{"id":"doi:10.1016/j.bspc.2024.106261","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.bspc.2024.106261","pdf_url":null,"source":{"id":"https://openalex.org/S8427965","display_name":"Biomedical Signal Processing and Control","issn_l":"1746-8094","issn":["1746-8094","1746-8108"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Biomedical Signal Processing and Control","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.bspc.2024.106261","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087612187","display_name":"Takayuki Hoshino","orcid":"https://orcid.org/0000-0001-5653-6670"},"institutions":[{"id":"https://openalex.org/I4210141715","display_name":"Keio University Shonan Fujisawa","ror":"https://ror.org/047khpn70","country_code":"JP","type":"education","lineage":["https://openalex.org/I4210141715"]},{"id":"https://openalex.org/I73613424","display_name":"National Institute of Advanced Industrial Science and Technology","ror":"https://ror.org/01703db54","country_code":"JP","type":"government","lineage":["https://openalex.org/I73613424"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Takayuki Hoshino","raw_affiliation_strings":["Keio University, 5322 Endo, Fujisawa-shi, Kanagawa 252-0882, Japan","National Institute of Advanced Industrial Science and Technology (AIST), 2-3-26 Aomi, Koto-ku, Tokyo 135-0064, Japan"],"affiliations":[{"raw_affiliation_string":"Keio University, 5322 Endo, Fujisawa-shi, Kanagawa 252-0882, Japan","institution_ids":["https://openalex.org/I4210141715"]},{"raw_affiliation_string":"National Institute of Advanced Industrial Science and Technology (AIST), 2-3-26 Aomi, Koto-ku, Tokyo 135-0064, Japan","institution_ids":["https://openalex.org/I73613424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025266672","display_name":"Suguru Kanoga","orcid":"https://orcid.org/0000-0002-2214-3622"},"institutions":[{"id":"https://openalex.org/I73613424","display_name":"National Institute of Advanced Industrial Science and Technology","ror":"https://ror.org/01703db54","country_code":"JP","type":"government","lineage":["https://openalex.org/I73613424"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Suguru Kanoga","raw_affiliation_strings":["National Institute of Advanced Industrial Science and Technology (AIST), 2-3-26 Aomi, Koto-ku, Tokyo 135-0064, Japan"],"affiliations":[{"raw_affiliation_string":"National Institute of Advanced Industrial Science and Technology (AIST), 2-3-26 Aomi, Koto-ku, Tokyo 135-0064, Japan","institution_ids":["https://openalex.org/I73613424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053163747","display_name":"Masashi Tsubaki","orcid":"https://orcid.org/0000-0002-5466-2195"},"institutions":[{"id":"https://openalex.org/I73613424","display_name":"National Institute of Advanced Industrial Science and Technology","ror":"https://ror.org/01703db54","country_code":"JP","type":"government","lineage":["https://openalex.org/I73613424"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masashi Tsubaki","raw_affiliation_strings":["National Institute of Advanced Industrial Science and Technology (AIST), 2-3-26 Aomi, Koto-ku, Tokyo 135-0064, Japan"],"affiliations":[{"raw_affiliation_string":"National Institute of Advanced Industrial Science and Technology (AIST), 2-3-26 Aomi, Koto-ku, Tokyo 135-0064, Japan","institution_ids":["https://openalex.org/I73613424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000591538","display_name":"Atsushi Aoyama","orcid":"https://orcid.org/0000-0003-2801-8467"},"institutions":[{"id":"https://openalex.org/I4210141715","display_name":"Keio University Shonan Fujisawa","ror":"https://ror.org/047khpn70","country_code":"JP","type":"education","lineage":["https://openalex.org/I4210141715"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Atsushi Aoyama","raw_affiliation_strings":["Keio University, 5322 Endo, Fujisawa-shi, Kanagawa 252-0882, Japan"],"affiliations":[{"raw_affiliation_string":"Keio University, 5322 Endo, Fujisawa-shi, Kanagawa 252-0882, Japan","institution_ids":["https://openalex.org/I4210141715"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5087612187"],"corresponding_institution_ids":["https://openalex.org/I4210141715","https://openalex.org/I73613424"],"apc_list":{"value":2420,"currency":"USD","value_usd":2420},"apc_paid":{"value":2420,"currency":"USD","value_usd":2420},"fwci":0.7822,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.66825984,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"94","issue":null,"first_page":"106261","last_page":"106261"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":1.0,"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":1.0,"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/T10338","display_name":"Advanced Sensor and Energy Harvesting Materials","score":0.991100013256073,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/multi-source","display_name":"Multi-source","score":0.8780053853988647},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7911080121994019},{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.6233204007148743},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5810918807983398},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5373330116271973},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5328083038330078},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.4880596399307251},{"id":"https://openalex.org/keywords/data-source","display_name":"Data source","score":0.47468850016593933},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45337459444999695},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.4345030188560486},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3562242388725281},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.087350994348526},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0788080096244812}],"concepts":[{"id":"https://openalex.org/C2780665216","wikidata":"https://www.wikidata.org/wiki/Q6934498","display_name":"Multi-source","level":2,"score":0.8780053853988647},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7911080121994019},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.6233204007148743},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5810918807983398},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5373330116271973},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5328083038330078},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.4880596399307251},{"id":"https://openalex.org/C2983685735","wikidata":"https://www.wikidata.org/wiki/Q5227355","display_name":"Data source","level":2,"score":0.47468850016593933},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45337459444999695},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.4345030188560486},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3562242388725281},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.087350994348526},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0788080096244812},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.bspc.2024.106261","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.bspc.2024.106261","pdf_url":null,"source":{"id":"https://openalex.org/S8427965","display_name":"Biomedical Signal Processing and Control","issn_l":"1746-8094","issn":["1746-8094","1746-8108"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Biomedical Signal Processing and Control","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/j.bspc.2024.106261","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.bspc.2024.106261","pdf_url":null,"source":{"id":"https://openalex.org/S8427965","display_name":"Biomedical Signal Processing and Control","issn_l":"1746-8094","issn":["1746-8094","1746-8108"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Biomedical Signal Processing and Control","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1487444243","display_name":null,"funder_award_id":"JP23H03445","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320320909","display_name":"Keio University","ror":"https://ror.org/02kn6nx58"},{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W1731081199","https://openalex.org/W1981856696","https://openalex.org/W2002055708","https://openalex.org/W2003228697","https://openalex.org/W2053998966","https://openalex.org/W2106526692","https://openalex.org/W2123167643","https://openalex.org/W2137502844","https://openalex.org/W2156654664","https://openalex.org/W2165698076","https://openalex.org/W2168162876","https://openalex.org/W2169931829","https://openalex.org/W2183161252","https://openalex.org/W2187089797","https://openalex.org/W2346062110","https://openalex.org/W2395579298","https://openalex.org/W2418845879","https://openalex.org/W2500302207","https://openalex.org/W2564000375","https://openalex.org/W2566079294","https://openalex.org/W2618146632","https://openalex.org/W2762706434","https://openalex.org/W2767187792","https://openalex.org/W2883837148","https://openalex.org/W2912885887","https://openalex.org/W2926366943","https://openalex.org/W2944759861","https://openalex.org/W2961171850","https://openalex.org/W2962879438","https://openalex.org/W2979689127","https://openalex.org/W3010034261","https://openalex.org/W3043248516","https://openalex.org/W3080342482","https://openalex.org/W3082568354","https://openalex.org/W3168220571","https://openalex.org/W3176638258","https://openalex.org/W4206784770","https://openalex.org/W4212999196","https://openalex.org/W4220835975","https://openalex.org/W4285124323","https://openalex.org/W4286908854","https://openalex.org/W4299518610","https://openalex.org/W4303474672","https://openalex.org/W4308178938","https://openalex.org/W4313598863","https://openalex.org/W4366310739","https://openalex.org/W4388213946","https://openalex.org/W6637618735","https://openalex.org/W6682132143","https://openalex.org/W6720111944","https://openalex.org/W6760844617","https://openalex.org/W6804569896","https://openalex.org/W6846630974","https://openalex.org/W6847803556"],"related_works":["https://openalex.org/W4385398839","https://openalex.org/W4384700341","https://openalex.org/W4394759804","https://openalex.org/W2269472958","https://openalex.org/W3140644504","https://openalex.org/W4287240320","https://openalex.org/W3173251459","https://openalex.org/W2998705539","https://openalex.org/W2990163449","https://openalex.org/W2576964996"],"abstract_inverted_index":{"Fine-tuning":[0],"(FT)":[1],"is":[2,94,110,114],"an":[3],"well-establish":[4],"transfer":[5],"learning":[6],"technique":[7,31],"that":[8,151,189],"mitigates":[9],"differences":[10],"in":[11,46,96,104,183,212],"data":[12,51],"distributions":[13],"of":[14,22,49,88,165,210],"target":[15],"and":[16,76,122,133,146,195],"source":[17,28,69,83],"domains":[18],"by":[19],"modifying":[20],"parameters":[21],"a":[23,72,86,105,202],"neural":[24],"network":[25],"pretrained":[26],"with":[27,201],"data.":[29],"This":[30,187],"has":[32],"been":[33],"demonstrated":[34],"to":[35,60],"be":[36,199],"effective":[37,194],"for":[38,100],"cross-subject":[39],"classification":[40],"using":[41],"surface":[42],"electromyograms":[43],"(sEMGs).":[44],"However,":[45],"the":[47,97,101,119,152,157,166,208],"case":[48],"biomedical":[50],"such":[52],"as":[53,71,85],"sEMGs,":[54],"there":[55,93],"are":[56,193],"two":[57],"possible":[58],"approaches":[59,125,155,192],"applying":[61],"FT:":[62],"(1)":[63],"single-source":[64,120,159],"approach,":[65,79],"which":[66,80,112],"uses":[67,81],"multiple":[68,82,89],"subjects":[70,84],"large":[73],"single":[74],"dataset,":[75],"(2)":[77],"multi-source":[78,106,124,154,191],"collection":[87],"small":[90],"datasets.":[91,186],"Furthermore,":[92],"arbitrariness":[95],"ensemble":[98,167,178],"strategy":[99],"final":[102],"output":[103],"approach.":[107],"As":[108],"it":[109],"unclear":[111],"approach":[113,121,160],"more":[115],"valid,":[116],"we":[117,171],"compared":[118],"four":[123],"(using":[126],"hard":[127],"voting,":[128,130,132],"soft":[129],"weighted":[131,135],"supervised":[134],"voting)":[136],"based":[137],"on":[138,161],"three":[139],"public":[140],"sEMG":[141],"datasets:":[142],"MyoDataset,":[143],"NinaPro":[144,147],"DB2,":[145],"DB5.":[148],"We":[149],"found":[150],"fine-tuned":[153,158,190],"outperformed":[156],"all":[162],"datasets":[163],"regardless":[164],"strategies.":[168],"In":[169],"addition,":[170],"identified":[172],"slight":[173],"but":[174,180],"significant":[175],"disparities":[176],"between":[177],"strategies,":[179],"this":[181],"varied":[182],"trend":[184],"across":[185],"suggests":[188],"better":[196],"performance":[197],"can":[198],"achieved":[200],"suitable":[203],"strategy.":[204],"Our":[205],"findings":[206],"improve":[207],"usefulness":[209],"FT":[211],"sEMG-based":[213],"human\u2013computer":[214],"interfaces.":[215]},"counts_by_year":[{"year":2025,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}