{"id":"https://openalex.org/W2585812517","doi":"https://doi.org/10.1109/icinfa.2016.7832011","title":"Recognition system of finger motion pattern based on AR model coefficient estimation","display_name":"Recognition system of finger motion pattern based on AR model coefficient estimation","publication_year":2016,"publication_date":"2016-08-01","ids":{"openalex":"https://openalex.org/W2585812517","doi":"https://doi.org/10.1109/icinfa.2016.7832011","mag":"2585812517"},"language":"en","primary_location":{"id":"doi:10.1109/icinfa.2016.7832011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icinfa.2016.7832011","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Information and Automation (ICIA)","raw_type":"proceedings-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/A5101893008","display_name":"Dianchun Bai","orcid":"https://orcid.org/0000-0001-5642-9605"},"institutions":[{"id":"https://openalex.org/I157507598","display_name":"Shenyang University of Technology","ror":"https://ror.org/00d7f8730","country_code":"CN","type":"education","lineage":["https://openalex.org/I157507598"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dianchun Bai","raw_affiliation_strings":["School of Electrical Engineering, Shenyang University of Technology, Shenyang, Liaoning Province, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Shenyang University of Technology, Shenyang, Liaoning Province, China","institution_ids":["https://openalex.org/I157507598"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021973157","display_name":"Zhang Shouxian","orcid":null},"institutions":[{"id":"https://openalex.org/I157507598","display_name":"Shenyang University of Technology","ror":"https://ror.org/00d7f8730","country_code":"CN","type":"education","lineage":["https://openalex.org/I157507598"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shouxian Zhang","raw_affiliation_strings":["School of Electrical Engineering, Shenyang University of Technology, Shenyang, Liaoning Province, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Shenyang University of Technology, Shenyang, Liaoning Province, China","institution_ids":["https://openalex.org/I157507598"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101428468","display_name":"Junyou Yang","orcid":"https://orcid.org/0000-0002-7890-7206"},"institutions":[{"id":"https://openalex.org/I157507598","display_name":"Shenyang University of Technology","ror":"https://ror.org/00d7f8730","country_code":"CN","type":"education","lineage":["https://openalex.org/I157507598"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junyou Yang","raw_affiliation_strings":["School of Electrical Engineering, Shenyang University of Technology, Shenyang, Liaoning Province, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Shenyang University of Technology, Shenyang, Liaoning Province, China","institution_ids":["https://openalex.org/I157507598"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076935808","display_name":"Yinlai Jiang","orcid":"https://orcid.org/0000-0002-0825-6444"},"institutions":[{"id":"https://openalex.org/I20529979","display_name":"University of Electro-Communications","ror":"https://ror.org/02x73b849","country_code":"JP","type":"education","lineage":["https://openalex.org/I20529979"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yinlai Jiang","raw_affiliation_strings":["Department of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications, Chofu, Tokyo, Japan","Department of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications, Chofu, TokYo, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications, Chofu, Tokyo, Japan","institution_ids":["https://openalex.org/I20529979"]},{"raw_affiliation_string":"Department of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications, Chofu, TokYo, Japan","institution_ids":["https://openalex.org/I20529979"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057191362","display_name":"Hiroshi Yokoi","orcid":"https://orcid.org/0000-0001-8571-1175"},"institutions":[{"id":"https://openalex.org/I20529979","display_name":"University of Electro-Communications","ror":"https://ror.org/02x73b849","country_code":"JP","type":"education","lineage":["https://openalex.org/I20529979"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroshi Yokoi","raw_affiliation_strings":["Department of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications, Chofu, Tokyo, Japan","Department of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications, Chofu, TokYo, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications, Chofu, Tokyo, Japan","institution_ids":["https://openalex.org/I20529979"]},{"raw_affiliation_string":"Department of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications, Chofu, TokYo, Japan","institution_ids":["https://openalex.org/I20529979"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101893008"],"corresponding_institution_ids":["https://openalex.org/I157507598"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15990765,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2016","issue":null,"first_page":"1249","last_page":"1254"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9958000183105469,"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9735999703407288,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6638298630714417},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6619092226028442},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.6573508977890015},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6002181172370911},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5737234354019165},{"id":"https://openalex.org/keywords/electromyography","display_name":"Electromyography","score":0.4963434338569641},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.4807453155517578},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.43545252084732056},{"id":"https://openalex.org/keywords/independent-component-analysis","display_name":"Independent component analysis","score":0.4246973991394043},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4185773730278015},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.41710710525512695},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2942468523979187},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.11803892254829407},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10860335826873779}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6638298630714417},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6619092226028442},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.6573508977890015},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6002181172370911},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5737234354019165},{"id":"https://openalex.org/C2777515770","wikidata":"https://www.wikidata.org/wiki/Q507369","display_name":"Electromyography","level":2,"score":0.4963434338569641},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.4807453155517578},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.43545252084732056},{"id":"https://openalex.org/C51432778","wikidata":"https://www.wikidata.org/wiki/Q1259145","display_name":"Independent component analysis","level":2,"score":0.4246973991394043},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4185773730278015},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.41710710525512695},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2942468523979187},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.11803892254829407},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10860335826873779},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icinfa.2016.7832011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icinfa.2016.7832011","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Information and Automation (ICIA)","raw_type":"proceedings-article"},{"id":"mag:2753062735","is_oa":false,"landing_page_url":"http://jglobal.jst.go.jp/en/public/201702272762297831","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W61707987","https://openalex.org/W1973013564","https://openalex.org/W1996602610","https://openalex.org/W2002426744","https://openalex.org/W2011457905","https://openalex.org/W2015814077","https://openalex.org/W2055552380","https://openalex.org/W2061273112","https://openalex.org/W2122936696","https://openalex.org/W2133644836","https://openalex.org/W2136143272","https://openalex.org/W2574524654","https://openalex.org/W6679902297"],"related_works":["https://openalex.org/W2121429698","https://openalex.org/W2182042810","https://openalex.org/W4252230435","https://openalex.org/W55679925","https://openalex.org/W3080404860","https://openalex.org/W2046761971","https://openalex.org/W3144722888","https://openalex.org/W2364896863","https://openalex.org/W2389189059","https://openalex.org/W4288804231"],"abstract_inverted_index":{"A":[0,48],"new":[1,49],"type":[2],"of":[3,19,58,62,90,127],"finger":[4,142,146,170],"articulation":[5],"angle":[6],"recognition":[7,168],"system":[8],"based":[9,72],"on":[10,73],"surface":[11],"electromyography":[12],"(sEMG)":[13],"signals":[14,36],"were":[15,51,133],"established.":[16],"Especially,":[17],"velocities":[18,126],"fingers":[20,128],"can":[21],"be":[22],"effectively":[23],"predicted":[24],"with":[25],"a":[26,107,163,174],"few":[27],"sEMG":[28,35],"channels.":[29],"This":[30],"paper":[31],"mainly":[32],"collected":[33,134],"the":[34,59,63,74,82,91,114,121,153],"during":[37],"forefinger":[38],"motions":[39],"which":[40,53],"are":[41,123],"slow,":[42],"medium":[43],"and":[44,85,113,152,167,173],"fast":[45,66],"velocities,":[46],"respectively.":[47],"method":[50],"proposed":[52],"acquired":[54,83],"more":[55],"accurate":[56],"estimate":[57],"velocity":[60],"variations":[61],"finger.":[64],"Firstly,":[65],"Independent":[67],"Component":[68],"Analysis":[69],"(FastICA)":[70],"algorithm":[71,99],"largest":[75],"negative":[76],"entropy":[77],"was":[78,100,111,160],"used":[79,101,161],"to":[80,102,165],"predict":[81],"signals,":[84],"then":[86],"separate":[87],"effective":[88],"operation":[89],"signals.":[92],"Then":[93],"autoregressive":[94],"(AR)":[95],"parameter":[96],"model":[97],"U-C":[98],"extract":[103],"characteristic":[104,119],"coefficient.":[105],"Finally,":[106],"RBF":[108,157],"neural":[109,158],"network":[110,159],"designed,":[112],"input":[115],"is":[116],"computational":[117],"AR":[118],"coefficient,":[120],"outputs":[122],"three":[124],"different":[125,169],"motion.":[129],"The":[130],"experiment":[131],"data":[132],"from":[135],"healthy":[136],"subjects'":[137],"four":[138],"muscles":[139],"including":[140],"Index":[141],"extensor":[143,147],"(IFE),":[144],"Middle":[145],"(MFE),":[148],"Palmaris":[149],"Longus":[150],"(PL)":[151],"flexor":[154],"carpi":[155],"(FC).":[156],"as":[162],"classifier":[164],"classification":[166],"movement":[171],"action,":[172],"satisfactory":[175],"results":[176],"has":[177],"achieved.":[178]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
