{"id":"https://openalex.org/W4406753699","doi":"https://doi.org/10.1109/tii.2024.3524799","title":"EMG Biometric Verification Via Disentangled Representations","display_name":"EMG Biometric Verification Via Disentangled Representations","publication_year":2025,"publication_date":"2025-01-23","ids":{"openalex":"https://openalex.org/W4406753699","doi":"https://doi.org/10.1109/tii.2024.3524799"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2024.3524799","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2024.3524799","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","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/A5010729887","display_name":"T.\u2010L. SU","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tanying Su","raw_affiliation_strings":["School of Information Science and Technology, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0007-8236-3364","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076568602","display_name":"Chenyun Dai","orcid":"https://orcid.org/0000-0002-3056-4339"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenyun Dai","raw_affiliation_strings":["School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-3056-4339","affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100441023","display_name":"Xiao Liu","orcid":"https://orcid.org/0000-0001-5514-021X"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Liu","raw_affiliation_strings":["School of Information Science and Technology, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-5514-021X","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015221002","display_name":"Xinyu Jiang","orcid":"https://orcid.org/0000-0002-8518-1415"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyu Jiang","raw_affiliation_strings":["School of Information Science and Technology, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-8518-1415","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5010729887"],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":0.6013,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.62326258,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"21","issue":"4","first_page":"3376","last_page":"3385"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.9936000108718872,"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":0.9936000108718872,"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9878000020980835,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9024999737739563,"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/biometrics","display_name":"Biometrics","score":0.7608327269554138},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7088634967803955},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2895393967628479}],"concepts":[{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.7608327269554138},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7088634967803955},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2895393967628479}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tii.2024.3524799","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2024.3524799","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.5299999713897705,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G3540468953","display_name":null,"funder_award_id":"62173094","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1995804323","https://openalex.org/W2076827014","https://openalex.org/W2092229687","https://openalex.org/W2100294832","https://openalex.org/W2952417223","https://openalex.org/W3001873791","https://openalex.org/W3006003538","https://openalex.org/W3019900571","https://openalex.org/W3030443594","https://openalex.org/W3034359740","https://openalex.org/W3035471470","https://openalex.org/W3037235457","https://openalex.org/W3046302181","https://openalex.org/W3083132452","https://openalex.org/W3091371329","https://openalex.org/W3101257721","https://openalex.org/W3158705359","https://openalex.org/W3162159851","https://openalex.org/W3197847961","https://openalex.org/W3202955105","https://openalex.org/W4225488023","https://openalex.org/W4285146467","https://openalex.org/W4285222931","https://openalex.org/W4312794561","https://openalex.org/W4385819951","https://openalex.org/W4386379577","https://openalex.org/W4387824516","https://openalex.org/W4389543176","https://openalex.org/W4393141114"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2076845124","https://openalex.org/W2183964146","https://openalex.org/W2379932303","https://openalex.org/W2095239294","https://openalex.org/W3147744369","https://openalex.org/W2062586268","https://openalex.org/W2019582947"],"abstract_inverted_index":{"Electromyography":[0],"(EMG)":[1],"with":[2,32,70,134,174,215],"individually":[3],"unique":[4],"characteristics,":[5],"has":[6],"emerged":[7],"as":[8,26],"a":[9,27,34,81,108,167],"promising":[10],"biometric":[11,19,41,56,72,152,170,207,237],"trait.":[12],"The":[13,40,102,113,128],"capability":[14],"to":[15,65,86,140,166,212,231],"further":[16],"encrypt":[17],"EMG":[18,30,55,63,68,90,169,234],"patterns":[20,51],"via":[21],"distinct":[22],"muscle":[23],"activities":[24],"(serve":[25],"password),":[28],"characterizes":[29],"biometrics":[31],"both":[33],"high":[35],"recognition":[36],"accuracy":[37],"and":[38,43,73,94,110,132],"revocability.":[39],"component":[42,46],"the":[44,49,71,88,142,178,196,201,204,206,221,228],"password":[45,74],"together":[47],"form":[48,66],"global":[50,67,89,179],"of":[52,145,189,218,223],"EMG.":[53],"Previous":[54],"verification":[57,153,171],"methods":[58],"directly":[59,176],"extracted":[60],"features":[61],"from":[62,162,177],"signals":[64],"representations":[69,91,116,164,235],"components":[75,96],"entangled":[76],"together.":[77],"In":[78],"this":[79,226],"work,":[80],"disentanglement":[82,103],"model":[83,104,129],"was":[84,105,130],"applied":[85],"disentangle":[87],"into":[92],"password-specific":[93],"biometric-specific":[95],"in":[97],"two":[98,114,121],"separate":[99],"latent":[100],"spaces.":[101],"built":[106],"on":[107,137],"multibranch-encoder":[109],"single-decoder":[111],"architecture.":[112],"disentangled":[115,163,233],"were":[117],"learned":[118],"separately":[119],"by":[120],"cascaded":[122],"support-vector":[123],"domain":[124],"description":[125],"(SVDD)":[126],"models.":[127],"trained":[131],"tested":[133],"data":[135],"acquired":[136],"different":[138],"days,":[139],"validate":[141],"interday":[143],"robustness":[144],"our":[146,224],"system,":[147],"which":[148],"is":[149,227],"important":[150],"for":[151,236],"using":[154],"variable":[155],"physiological":[156],"signals.":[157],"Results":[158],"demonstrated":[159],"that":[160],"learning":[161,175],"contributes":[165],"better":[168],"performance":[172],"compared":[173],"representation.":[180],"Our":[181],"method":[182],"achieved":[183],"an":[184,216],"Equal":[185],"Error":[186],"Rate":[187],"(EER)":[188],"0.0075":[190],"when":[191,200],"impostors":[192,202],"do":[193],"not":[194],"know":[195,203],"passwords.":[197],"Furthermore,":[198],"even":[199],"password,":[205],"defense":[208],"alone":[209],"still":[210],"managed":[211],"prevent":[213],"intrusion":[214],"EER":[217],"0.1582.":[219],"To":[220],"best":[222],"knowledge,":[225],"first":[229],"study":[230],"employ":[232],"verification.":[238]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
