{"id":"https://openalex.org/W4312829785","doi":"https://doi.org/10.1109/access.2022.3217910","title":"CSI-DeepNet: A Lightweight Deep Convolutional Neural Network Based Hand Gesture Recognition System Using Wi-Fi CSI Signal","display_name":"CSI-DeepNet: A Lightweight Deep Convolutional Neural Network Based Hand Gesture Recognition System Using Wi-Fi CSI Signal","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312829785","doi":"https://doi.org/10.1109/access.2022.3217910"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3217910","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3217910","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09931675.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09931675.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101836514","display_name":"M. Humayun Kabir","orcid":"https://orcid.org/0000-0002-6849-2051"},"institutions":[{"id":"https://openalex.org/I57664883","display_name":"Ajou University","ror":"https://ror.org/03tzb2h73","country_code":"KR","type":"education","lineage":["https://openalex.org/I57664883"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"M. Humayun Kabir","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Ajou University, Suwon, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Ajou University, Suwon, Republic of Korea","institution_ids":["https://openalex.org/I57664883"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016659981","display_name":"Md. Ali Hasan","orcid":"https://orcid.org/0000-0003-4503-4864"},"institutions":[{"id":"https://openalex.org/I57664883","display_name":"Ajou University","ror":"https://ror.org/03tzb2h73","country_code":"KR","type":"education","lineage":["https://openalex.org/I57664883"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Md. Ali Hasan","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Ajou University, Suwon, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Ajou University, Suwon, Republic of Korea","institution_ids":["https://openalex.org/I57664883"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009725517","display_name":"Wonjae Shin","orcid":"https://orcid.org/0000-0001-6513-1237"},"institutions":[{"id":"https://openalex.org/I57664883","display_name":"Ajou University","ror":"https://ror.org/03tzb2h73","country_code":"KR","type":"education","lineage":["https://openalex.org/I57664883"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Wonjae Shin","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Ajou University, Suwon, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0001-6513-1237","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Ajou University, Suwon, Republic of Korea","institution_ids":["https://openalex.org/I57664883"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101836514"],"corresponding_institution_ids":["https://openalex.org/I57664883"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.5695,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.8286735,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"10","issue":null,"first_page":"114787","last_page":"114801"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":1.0,"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":1.0,"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/T10860","display_name":"Speech and Audio Processing","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9936000108718872,"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/computer-science","display_name":"Computer science","score":0.8579741716384888},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6510381698608398},{"id":"https://openalex.org/keywords/gesture-recognition","display_name":"Gesture recognition","score":0.6459569931030273},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6358705163002014},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5971461534500122},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5893247127532959},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5171982049942017},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.4964218735694885},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47534963488578796},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.4666720926761627},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4549708664417267},{"id":"https://openalex.org/keywords/gesture","display_name":"Gesture","score":0.4115787148475647},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.32923269271850586},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.2952694296836853},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.11961841583251953}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8579741716384888},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6510381698608398},{"id":"https://openalex.org/C159437735","wikidata":"https://www.wikidata.org/wiki/Q1519524","display_name":"Gesture recognition","level":3,"score":0.6459569931030273},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6358705163002014},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5971461534500122},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5893247127532959},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5171982049942017},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.4964218735694885},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47534963488578796},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.4666720926761627},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4549708664417267},{"id":"https://openalex.org/C207347870","wikidata":"https://www.wikidata.org/wiki/Q371174","display_name":"Gesture","level":2,"score":0.4115787148475647},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.32923269271850586},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2952694296836853},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.11961841583251953},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3217910","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3217910","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09931675.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:afdd4e2453a64116b65c5ad9895a7dc3","is_oa":true,"landing_page_url":"https://doaj.org/article/afdd4e2453a64116b65c5ad9895a7dc3","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 10, Pp 114787-114801 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3217910","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3217910","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09931675.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5400000214576721}],"awards":[{"id":"https://openalex.org/G3212871455","display_name":null,"funder_award_id":"2021R1A4A1030775","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G4388520830","display_name":null,"funder_award_id":"2022R1A2C4002065","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1572711505","https://openalex.org/W1965403160","https://openalex.org/W1965602597","https://openalex.org/W1983705368","https://openalex.org/W2054780155","https://openalex.org/W2089695767","https://openalex.org/W2115612038","https://openalex.org/W2129045955","https://openalex.org/W2286276551","https://openalex.org/W2338892592","https://openalex.org/W2594265094","https://openalex.org/W2794264461","https://openalex.org/W2944172587","https://openalex.org/W2944605902","https://openalex.org/W2952586546","https://openalex.org/W2963495494","https://openalex.org/W2980714463","https://openalex.org/W3002717429","https://openalex.org/W3005472058","https://openalex.org/W3048617177","https://openalex.org/W3091100426","https://openalex.org/W3097728828","https://openalex.org/W3117335872","https://openalex.org/W3153796060","https://openalex.org/W4206744836","https://openalex.org/W4226424792","https://openalex.org/W4297775537","https://openalex.org/W6631190155","https://openalex.org/W6737664043"],"related_works":["https://openalex.org/W2902873204","https://openalex.org/W2185750513","https://openalex.org/W2010878661","https://openalex.org/W3147379364","https://openalex.org/W2026258298","https://openalex.org/W3204639664","https://openalex.org/W2970836791","https://openalex.org/W2805039731","https://openalex.org/W2989699735","https://openalex.org/W3174643231"],"abstract_inverted_index":{"Hand":[0],"gesture":[1,74,111],"is":[2,43,138,146,223],"a":[3,31,69,98,168,176],"visual":[4],"input":[5],"of":[6,34,121,128,215],"human-computer":[7],"interaction":[8],"for":[9,46,103],"providing":[10],"different":[11],"applications":[12],"in":[13,48,153,204],"smart":[14],"homes,":[15],"healthcare,":[16],"and":[17,93,181,233],"eldercare.":[18],"Most":[19],"deep":[20,72,235],"learning-based":[21,73],"techniques":[22],"adopt":[23],"standard":[24],"convolution":[25],"neural":[26,172],"networks":[27],"(CNNs)":[28],"which":[29,222],"require":[30],"large":[32],"number":[33],"model":[35,56,195],"parameters":[36,57],"with":[37,50,118,135,150,175,217],"high":[38],"computational":[39,52,220],"complexity;":[40],"thus,":[41],"it":[42],"not":[44],"suitable":[45],"application":[47],"devices":[49],"limited":[51],"resources.":[53],"However,":[54],"fewer":[55,194],"can":[58],"reduce":[59],"the":[60,104,125,144,154,161,191,198,205,226],"system":[61,210],"accuracy.":[62],"To":[63],"address":[64],"this":[65],"challenge,":[66],"we":[67],"propose":[68],"lightweight":[70],"heterogeneous":[71],"recognition":[75],"system,":[76],"coined":[77],"CSI-DeepNet.":[78],"The":[79,163,208],"CSI-DeepNet":[80],"comprises":[81],"four":[82],"steps:":[83],"i)":[84],"data":[85,88,127,145,155],"collection,":[86],"ii)":[87],"processing,":[89],"iii)":[90],"feature":[91,164,177],"extraction,":[92],"iv)":[94],"classification.":[95],"We":[96],"utilize":[97],"low-power":[99],"system-on-chip":[100],"(SoC),":[101],"ESP-32,":[102],"first":[105],"time":[106],"to":[107,140,160,185],"collect":[108],"alphanumeric":[109],"hand":[110],"datasets":[112],"using":[113,193,229,238],"channel":[114],"state":[115],"information":[116],"(CSI)":[117],"1,800":[119],"trials":[120],"20":[122],"gestures,":[123],"including":[124],"steady-state":[126],"ten":[129],"people.":[130],"A":[131],"Butterworth":[132],"low-pass":[133],"filter":[134],"Gaussian":[136],"smoothing":[137],"applied":[139],"remove":[141],"noise;":[142],"subsequently,":[143],"split":[147],"into":[148],"windows":[149],"sufficient":[151],"dimensions":[152],"processing":[156],"step":[157],"before":[158],"feeding":[159],"model.":[162],"extraction":[165],"section":[166],"utilizes":[167],"depthwise":[169],"separable":[170],"convolutional":[171],"network":[173],"(DS-Conv)":[174],"attention":[178],"(FA)":[179],"block":[180,183],"residual":[182],"(RB)":[184],"extract":[186],"fine-grained":[187],"features":[188,201],"while":[189],"reducing":[190],"complexity":[192],"parameters.":[196],"Finally,":[197],"extracted":[199],"refined":[200],"are":[202],"classified":[203],"classification":[206],"section.":[207],"proposed":[209],"achieves":[211],"an":[212],"average":[213],"accuracy":[214],"96.31%":[216],"much":[218],"less":[219],"complexity,":[221],"better":[224],"than":[225],"results":[227],"obtained":[228],"state-of-the-art":[230],"pre-trained":[231],"CNNs":[232],"two":[234],"learning":[236],"models":[237],"CSI":[239],"data.":[240]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":1}],"updated_date":"2026-05-19T21:40:30.786675","created_date":"2025-10-10T00:00:00"}