{"id":"https://openalex.org/W4377089546","doi":"https://doi.org/10.1109/ner52421.2023.10123842","title":"Privacy-Preserving Motor Intent Classification via Feature Disentanglement","display_name":"Privacy-Preserving Motor Intent Classification via Feature Disentanglement","publication_year":2023,"publication_date":"2023-04-24","ids":{"openalex":"https://openalex.org/W4377089546","doi":"https://doi.org/10.1109/ner52421.2023.10123842"},"language":"en","primary_location":{"id":"doi:10.1109/ner52421.2023.10123842","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ner52421.2023.10123842","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5009024629","display_name":"Jiahao Fan","orcid":"https://orcid.org/0000-0003-0514-1323"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiahao Fan","raw_affiliation_strings":["The Pennsylvania State University,Mechanical Engineering,State College,PA,U.S","Mechanical Engineering, The Pennsylvania State University, State College, PA, U.S"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Pennsylvania State University,Mechanical Engineering,State College,PA,U.S","institution_ids":["https://openalex.org/I130769515"]},{"raw_affiliation_string":"Mechanical Engineering, The Pennsylvania State University, State College, PA, U.S","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050076687","display_name":"Xiaogang Hu","orcid":"https://orcid.org/0000-0002-8565-5940"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaogang Hu","raw_affiliation_strings":["The Pennsylvania State University,Mechanical Engineering,State College,PA,U.S","Mechanical Engineering, The Pennsylvania State University, State College, PA, U.S"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Pennsylvania State University,Mechanical Engineering,State College,PA,U.S","institution_ids":["https://openalex.org/I130769515"]},{"raw_affiliation_string":"Mechanical Engineering, The Pennsylvania State University, State College, PA, U.S","institution_ids":["https://openalex.org/I130769515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130769515"],"apc_list":null,"apc_paid":null,"fwci":1.3031,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.75224425,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9984999895095825,"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/T11601","display_name":"Neuroscience and Neural Engineering","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/2804","display_name":"Cellular and Molecular 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/computer-science","display_name":"Computer science","score":0.789269208908081},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6196405291557312},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.609748125076294},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5630612373352051},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.5482580661773682},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5240795016288757},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.509760320186615},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.49196574091911316},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4689110517501831},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4662932753562927},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4287789762020111},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.42158833146095276},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09457430243492126}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.789269208908081},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6196405291557312},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.609748125076294},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5630612373352051},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.5482580661773682},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5240795016288757},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.509760320186615},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.49196574091911316},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4689110517501831},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4662932753562927},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4287789762020111},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.42158833146095276},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09457430243492126},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ner52421.2023.10123842","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ner52421.2023.10123842","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5299999713897705,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G3664630799","display_name":null,"funder_award_id":"W81XWH-21-1-0185","funder_id":"https://openalex.org/F4320306078","funder_display_name":"U.S. Department of Defense"},{"id":"https://openalex.org/G6201944124","display_name":"CAREER: Robust Decoding of Neural Command for Real Time Human Machine Interactions","funder_award_id":"1847319","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306078","display_name":"U.S. Department of Defense","ror":"https://ror.org/0447fe631"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2093265755","https://openalex.org/W2106526692","https://openalex.org/W2409983459","https://openalex.org/W2488164446","https://openalex.org/W2962879438","https://openalex.org/W3158705359","https://openalex.org/W3162159851","https://openalex.org/W3202955105","https://openalex.org/W4285146467"],"related_works":["https://openalex.org/W2055243143","https://openalex.org/W2062195135","https://openalex.org/W4321636575","https://openalex.org/W1986418932","https://openalex.org/W2357796999","https://openalex.org/W2045526782","https://openalex.org/W2741131631","https://openalex.org/W2156919374","https://openalex.org/W1984019423","https://openalex.org/W2795079307"],"abstract_inverted_index":{"Recent":[0],"studies":[1,31],"have":[2],"revealed":[3,188],"that":[4,146,189,208],"sensitive":[5,76,117],"and":[6,39,61,136,164],"private":[7],"attributes":[8,77,118],"could":[9],"be":[10],"decoded":[11],"from":[12,99,131],"surface":[13],"electromyogram":[14],"(sEMG)":[15],"signals,":[16],"which":[17],"can":[18],"incur":[19],"privacy":[20],"threat":[21],"to":[22,51,65,74,112,160,194],"the":[23,37,82,95,107,114,147,152,161,170,190],"users":[24],"of":[25,41,116,155,211],"sEMG-based":[26,67],"pattern":[27,90,109],"recognition":[28,91,110,184,222],"applications.":[29,223],"Most":[30],"so":[32],"far":[33],"focus":[34],"on":[35,129],"improving":[36],"accuracy":[38,197],"reliability":[40],"sEMG":[42,83,101,212],"classifiers,":[43],"but":[44],"much":[45],"less":[46],"attention":[47],"has":[48],"been":[49],"paid":[50],"their":[52],"privacy.":[53],"To":[54],"fill":[55],"this":[56,58],"gap,":[57],"study":[59],"implemented":[60],"evaluated":[62,128,180],"a":[63,215],"framework":[64],"optimize":[66],"data-sharing":[68],"mechanism.":[69],"Our":[70,143,186],"primary":[71,89],"goal":[72],"was":[73,127,178],"remove":[75],"(i.e.,":[78],"identity-relevant":[79],"information)":[80],"in":[81,181],"features":[84],"before":[85],"sharing":[86],"them":[87],"with":[88,106,134,201],"tasks.":[92,185],"We":[93,103],"disentangled":[94,148,176,191,209],"identity-insensitive,":[96],"task-relevant":[97],"representations":[98,149,167,192,210],"original":[100,162],"features.":[102],"shared":[104],"it":[105],"downstream":[108],"tasks":[111],"reduce":[113],"chance":[115],"being":[119],"inferred":[120],"by":[121,169],"potential":[122],"attackers.":[123],"The":[124,175],"proposed":[125],"method":[126],"data":[130,138],"twenty":[132],"subjects,":[133],"training":[135],"testing":[137],"acquired":[139],"3\u201325":[140],"days":[141],"apart.":[142],"results":[144,187],"showed":[145],"significantly":[150],"reduced":[151],"success":[153],"rate":[154],"identity":[156],"inference":[157],"attacks":[158],"compared":[159,200],"feature":[163,172,203],"its":[165],"sparse":[166],"generated":[168],"state-of-the-art":[171],"projection":[173],"methods.":[174],"representation":[177],"then":[179],"hand":[182],"gesture":[183],"led":[193],"higher":[195],"classification":[196],"across":[198],"classifiers":[199],"other":[202],"implementations.":[204],"This":[205],"work":[206],"shows":[207],"signals":[213],"are":[214],"promising":[216],"solution":[217],"for":[218],"privacy-preserving":[219],"motor":[220],"intent":[221]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-08-06T08:24:18.245995","created_date":"2025-10-10T00:00:00"}