{"id":"https://openalex.org/W4211198859","doi":"https://doi.org/10.1109/ccnc49033.2022.9700590","title":"Location Independent Gesture Recognition Using Channel State Information","display_name":"Location Independent Gesture Recognition Using Channel State Information","publication_year":2022,"publication_date":"2022-01-08","ids":{"openalex":"https://openalex.org/W4211198859","doi":"https://doi.org/10.1109/ccnc49033.2022.9700590"},"language":"en","primary_location":{"id":"doi:10.1109/ccnc49033.2022.9700590","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccnc49033.2022.9700590","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 19th Annual Consumer Communications &amp; Networking Conference (CCNC)","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/A5036710007","display_name":"Israel Elujide","orcid":null},"institutions":[{"id":"https://openalex.org/I189196454","display_name":"The University of Texas at Arlington","ror":"https://ror.org/019kgqr73","country_code":"US","type":"education","lineage":["https://openalex.org/I189196454"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Israel Elujide","raw_affiliation_strings":["The University of Texas at Arlington,Dept. of Computer Science &#x0026; Engineering,USA"],"affiliations":[{"raw_affiliation_string":"The University of Texas at Arlington,Dept. of Computer Science &#x0026; Engineering,USA","institution_ids":["https://openalex.org/I189196454"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078386920","display_name":"Chunhai Feng","orcid":"https://orcid.org/0000-0002-9670-922X"},"institutions":[{"id":"https://openalex.org/I189196454","display_name":"The University of Texas at Arlington","ror":"https://ror.org/019kgqr73","country_code":"US","type":"education","lineage":["https://openalex.org/I189196454"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chunhai Feng","raw_affiliation_strings":["The University of Texas at Arlington,Dept. of Computer Science &#x0026; Engineering,USA"],"affiliations":[{"raw_affiliation_string":"The University of Texas at Arlington,Dept. of Computer Science &#x0026; Engineering,USA","institution_ids":["https://openalex.org/I189196454"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056009434","display_name":"Aref Shiran","orcid":null},"institutions":[{"id":"https://openalex.org/I189196454","display_name":"The University of Texas at Arlington","ror":"https://ror.org/019kgqr73","country_code":"US","type":"education","lineage":["https://openalex.org/I189196454"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aref Shiran","raw_affiliation_strings":["The University of Texas at Arlington,Dept. of Computer Science &#x0026; Engineering,USA"],"affiliations":[{"raw_affiliation_string":"The University of Texas at Arlington,Dept. of Computer Science &#x0026; Engineering,USA","institution_ids":["https://openalex.org/I189196454"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100402515","display_name":"Jian Li","orcid":"https://orcid.org/0000-0002-5749-2734"},"institutions":[{"id":"https://openalex.org/I189196454","display_name":"The University of Texas at Arlington","ror":"https://ror.org/019kgqr73","country_code":"US","type":"education","lineage":["https://openalex.org/I189196454"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jian Li","raw_affiliation_strings":["The University of Texas at Arlington,Dept. of Computer Science &#x0026; Engineering,USA"],"affiliations":[{"raw_affiliation_string":"The University of Texas at Arlington,Dept. of Computer Science &#x0026; Engineering,USA","institution_ids":["https://openalex.org/I189196454"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001033170","display_name":"Yonghe Liu","orcid":"https://orcid.org/0000-0003-2909-6088"},"institutions":[{"id":"https://openalex.org/I189196454","display_name":"The University of Texas at Arlington","ror":"https://ror.org/019kgqr73","country_code":"US","type":"education","lineage":["https://openalex.org/I189196454"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yonghe Liu","raw_affiliation_strings":["The University of Texas at Arlington,Dept. of Computer Science &#x0026; Engineering,USA"],"affiliations":[{"raw_affiliation_string":"The University of Texas at Arlington,Dept. of Computer Science &#x0026; Engineering,USA","institution_ids":["https://openalex.org/I189196454"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5036710007"],"corresponding_institution_ids":["https://openalex.org/I189196454"],"apc_list":null,"apc_paid":null,"fwci":0.2744,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.50655377,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"841","last_page":"846"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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":0.9998000264167786,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9945999979972839,"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/gesture","display_name":"Gesture","score":0.8619213700294495},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7929551601409912},{"id":"https://openalex.org/keywords/gesture-recognition","display_name":"Gesture recognition","score":0.7795615196228027},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5324597954750061},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5161641240119934},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4913257658481598},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.48586151003837585},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.48044058680534363},{"id":"https://openalex.org/keywords/channel-state-information","display_name":"Channel state information","score":0.4726898968219757},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46759316325187683},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.43849942088127136},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.43004661798477173},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.41806524991989136},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4127599000930786},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.38356688618659973},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.10389411449432373}],"concepts":[{"id":"https://openalex.org/C207347870","wikidata":"https://www.wikidata.org/wiki/Q371174","display_name":"Gesture","level":2,"score":0.8619213700294495},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7929551601409912},{"id":"https://openalex.org/C159437735","wikidata":"https://www.wikidata.org/wiki/Q1519524","display_name":"Gesture recognition","level":3,"score":0.7795615196228027},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5324597954750061},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5161641240119934},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4913257658481598},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.48586151003837585},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.48044058680534363},{"id":"https://openalex.org/C148063708","wikidata":"https://www.wikidata.org/wiki/Q5072511","display_name":"Channel state information","level":3,"score":0.4726898968219757},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46759316325187683},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.43849942088127136},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.43004661798477173},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.41806524991989136},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4127599000930786},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38356688618659973},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.10389411449432373},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccnc49033.2022.9700590","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccnc49033.2022.9700590","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 19th Annual Consumer Communications &amp; Networking Conference (CCNC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W273955616","https://openalex.org/W1966672755","https://openalex.org/W1969595749","https://openalex.org/W2089695767","https://openalex.org/W2095396347","https://openalex.org/W2164416728","https://openalex.org/W2473779510","https://openalex.org/W2527524423","https://openalex.org/W2619289925","https://openalex.org/W2794264461","https://openalex.org/W2794843057","https://openalex.org/W2808442904","https://openalex.org/W2811056467","https://openalex.org/W2886490782","https://openalex.org/W2887884062","https://openalex.org/W2897132279","https://openalex.org/W2904236804","https://openalex.org/W2950821050","https://openalex.org/W3104559109","https://openalex.org/W3119877017","https://openalex.org/W4289490880","https://openalex.org/W6610017368","https://openalex.org/W6754215057"],"related_works":["https://openalex.org/W2066003895","https://openalex.org/W2902873204","https://openalex.org/W2185750513","https://openalex.org/W3147379364","https://openalex.org/W2010878661","https://openalex.org/W2026258298","https://openalex.org/W3204639664","https://openalex.org/W2970836791","https://openalex.org/W2805039731","https://openalex.org/W2989699735"],"abstract_inverted_index":{"Gesture":[0],"recognition":[1,33,183,194,229],"has":[2],"been":[3],"the":[4,30,58,141,166,170,173,181,188,192],"subject":[5],"of":[6,61,113,146,191],"intensive":[7],"research":[8],"in":[9,76,128,213,216],"recent":[10,26],"years":[11],"owing":[12],"to":[13,57,133,154,164,176],"its":[14],"wide":[15],"applications.":[16],"Unlike":[17],"traditional":[18],"systems,":[19],"which":[20],"usually":[21],"require":[22,49],"wearable":[23],"sensors,":[24],"many":[25],"works":[27,47],"have":[28],"achieved":[29],"desirable":[31],"gesture":[32,100,120,182,193,228],"performance":[34],"using":[35],"wireless":[36],"channel":[37,62],"state":[38,63],"information":[39,95],"from":[40,96,137,206],"commercially":[41],"available":[42],"WiFi":[43],"devices.":[44],"However,":[45],"existing":[46],"generally":[48],"training":[50,81,171],"new":[51,78,83,236],"models":[52],"for":[53,99,180,235],"different":[54,211,220],"locations":[55,215],"due":[56],"location-dependent":[59,138],"nature":[60],"information.":[64],"This":[65],"paper":[66],"proposes":[67],"a":[68,77,82,116,147,203],"location-independent":[69,227],"system":[70,131,201,230],"that":[71,89,225],"can":[72,231],"recognize":[73],"gestures":[74,212],"performed":[75],"location":[79,91],"without":[80],"model.":[84],"Our":[85],"approach":[86],"uses":[87],"disentanglement":[88],"extricates":[90],"and":[92,122,184,195],"other":[93],"extraneous":[94],"those":[97],"needed":[98],"recognition.":[101],"The":[102,125,222],"implementation":[103],"is":[104,132,152],"based":[105],"on":[106],"an":[107,162],"unsupervised":[108],"invariance":[109],"induction":[110],"framework":[111],"consisting":[112,145],"feature":[114,142],"extraction,":[115],"multi-output":[117],"latent":[118,167],"space,":[119],"recognition,":[121],"decoder":[123,185,196],"modules.":[124,197],"key":[126],"idea":[127],"designing":[129],"this":[130],"separate":[134],"gesture-dependent":[135],"features":[136,178],"features.":[139],"Specifically,":[140],"extraction":[143],"module":[144],"long":[148],"short-term":[149],"memory":[150],"network":[151,174],"employed":[153],"select":[155],"representative":[156],"features;":[157],"it":[158],"essentially":[159],"serves":[160],"as":[161],"encoder":[163],"generate":[165],"space.":[168],"During":[169],"process,":[172],"learns":[175],"cluster":[177],"representation":[179],"by":[186],"minimizing":[187],"total":[189],"loss":[190],"We":[198],"test":[199],"our":[200,226],"with":[202,219],"dataset":[204],"collected":[205],"various":[207],"subjects":[208],"performing":[209],"four":[210],"multiple":[214],"seven":[217],"rooms":[218],"layouts.":[221],"results":[223],"show":[224],"achieve":[232],"88.69%":[233],"accuracy":[234],"locations.":[237]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
