{"id":"https://openalex.org/W4292387512","doi":"https://doi.org/10.1109/civemsa53371.2022.9853649","title":"Heuristic Application System on Pose Detection of Elderly Activity Using Machine Learning in Real-Time","display_name":"Heuristic Application System on Pose Detection of Elderly Activity Using Machine Learning in Real-Time","publication_year":2022,"publication_date":"2022-06-15","ids":{"openalex":"https://openalex.org/W4292387512","doi":"https://doi.org/10.1109/civemsa53371.2022.9853649"},"language":"en","primary_location":{"id":"doi:10.1109/civemsa53371.2022.9853649","is_oa":false,"landing_page_url":"https://doi.org/10.1109/civemsa53371.2022.9853649","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 9th International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","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/A5073761124","display_name":"Sofia Ariyani","orcid":null},"institutions":[{"id":"https://openalex.org/I4210108816","display_name":"Universitas Muhammadiyah Jember","ror":"https://ror.org/021p32893","country_code":"ID","type":"education","lineage":["https://openalex.org/I4210108816"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Sofia Ariyani","raw_affiliation_strings":["Universitas Muhammadiyah Jember,Department of Electrical Engineering,Jember,Indonesia","Department of Electrical Engineering, Universitas Muhammadiyah Jember, Jember, Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universitas Muhammadiyah Jember,Department of Electrical Engineering,Jember,Indonesia","institution_ids":["https://openalex.org/I4210108816"]},{"raw_affiliation_string":"Department of Electrical Engineering, Universitas Muhammadiyah Jember, Jember, Indonesia","institution_ids":["https://openalex.org/I4210108816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036919699","display_name":"Eko Mulyanto Yuniarno","orcid":"https://orcid.org/0000-0003-1243-3025"},"institutions":[{"id":"https://openalex.org/I16413167","display_name":"University of Surabaya","ror":"https://ror.org/013314927","country_code":"ID","type":"education","lineage":["https://openalex.org/I16413167"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Eko Mulyanto Yuniarno","raw_affiliation_strings":["Department of Computer Engineering,Department of Computer Engineering,Surabaya,Indonesia","Department of Computer Engineering, Department of Computer Engineering, Surabaya, Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering,Department of Computer Engineering,Surabaya,Indonesia","institution_ids":["https://openalex.org/I16413167"]},{"raw_affiliation_string":"Department of Computer Engineering, Department of Computer Engineering, Surabaya, Indonesia","institution_ids":["https://openalex.org/I16413167"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012595591","display_name":"Mauridhi Hery Purnomo","orcid":"https://orcid.org/0000-0002-6221-7382"},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Sepuluh Nopember Institute of Technology","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]},{"id":"https://openalex.org/I4210164862","display_name":"Artificial Intelligence in Medicine (Canada)","ror":"https://ror.org/05p590m36","country_code":"CA","type":"company","lineage":["https://openalex.org/I4210164862"]}],"countries":["CA","ID"],"is_corresponding":false,"raw_author_name":"Mauridhi Hery Purnomo","raw_affiliation_strings":["Institut Teknologi Sepuluh Nopember,Department of Electrical Engineering Department of Computer Engineering,Surabaya,Indonesia","Department of Electrical Engineering Department of Computer Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia","University Center of Excellence on Artificial Intelligence for Healthcare and Society"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut Teknologi Sepuluh Nopember,Department of Electrical Engineering Department of Computer Engineering,Surabaya,Indonesia","institution_ids":["https://openalex.org/I166843116"]},{"raw_affiliation_string":"Department of Electrical Engineering Department of Computer Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia","institution_ids":["https://openalex.org/I166843116"]},{"raw_affiliation_string":"University Center of Excellence on Artificial Intelligence for Healthcare and Society","institution_ids":["https://openalex.org/I4210164862"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4623,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.71777848,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.991599977016449,"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/T10510","display_name":"Stroke Rehabilitation and Recovery","score":0.9696999788284302,"subfield":{"id":"https://openalex.org/subfields/2742","display_name":"Rehabilitation"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7030184864997864},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.6745960712432861},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5296167135238647},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.5020768642425537},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.4820740818977356},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.4748523533344269},{"id":"https://openalex.org/keywords/landmark","display_name":"Landmark","score":0.43756037950515747},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43711405992507935},{"id":"https://openalex.org/keywords/elderly-people","display_name":"Elderly people","score":0.4370347261428833},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.41430792212486267},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33443403244018555},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.19531545042991638},{"id":"https://openalex.org/keywords/gerontology","display_name":"Gerontology","score":0.1331496238708496}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7030184864997864},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.6745960712432861},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5296167135238647},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5020768642425537},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.4820740818977356},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.4748523533344269},{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.43756037950515747},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43711405992507935},{"id":"https://openalex.org/C3018697994","wikidata":"https://www.wikidata.org/wiki/Q191089","display_name":"Elderly people","level":2,"score":0.4370347261428833},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.41430792212486267},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33443403244018555},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.19531545042991638},{"id":"https://openalex.org/C74909509","wikidata":"https://www.wikidata.org/wiki/Q10387","display_name":"Gerontology","level":1,"score":0.1331496238708496},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/civemsa53371.2022.9853649","is_oa":false,"landing_page_url":"https://doi.org/10.1109/civemsa53371.2022.9853649","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 9th International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.5899999737739563,"display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2064675550","https://openalex.org/W2611932403","https://openalex.org/W2612762156","https://openalex.org/W2788865504","https://openalex.org/W2801908962","https://openalex.org/W3158606038","https://openalex.org/W3210072454"],"related_works":["https://openalex.org/W2056853153","https://openalex.org/W2057559274","https://openalex.org/W2361278909","https://openalex.org/W2352536444","https://openalex.org/W2349982312","https://openalex.org/W2388605575","https://openalex.org/W3034765317","https://openalex.org/W2369577326","https://openalex.org/W2335190812","https://openalex.org/W4214937936"],"abstract_inverted_index":{"Many":[0],"developed":[1],"countries":[2],"have":[3,82,189],"a":[4,27,43,110,162],"population":[5,14],"of":[6,15,66,74,79,107,149,205],"elderly":[7,40,50,67,84,96],"people":[8,41],"that":[9,38,48],"is":[10,26,159],"greater":[11],"than":[12],"the":[13,21,35,49,119,122,134,147,156,194,203,206],"young":[16],"workers.":[17],"So.":[18],"To":[19,33],"meet":[20,34],"demand":[22,37],"for":[23,70,173,201],"labor":[24],"there":[25],"decline":[28,56],"because":[29],"many":[30,39],"are":[31],"retiring.":[32],"future":[36],"need":[42],"quality":[44],"care":[45],"service":[46],"so":[47],"who":[51],"experience":[52],"physical":[53,143],"and":[54,64,90,94,112,139,164,171,186],"cognitive":[55],"can":[57,128,198],"be":[58,199],"well":[59],"protected.":[60],"Great":[61],"potential":[62,114],"study":[63],"evaluation":[65],"movement":[68,85,97],"activity":[69,98],"healthcare.":[71],"The":[72,126],"algorithm":[73],"pose":[75,150],"estimation":[76,151],"takes":[77],"advantage":[78],"recording":[80,131],"video":[81,130],"tracked":[83],"automatically":[86],"using":[87],"camera":[88,207],"devices":[89],"computer":[91],"vision.":[92],"Monitoring":[93],"measuring":[95],"in":[99,133,152,161,187],"real-time":[100,188],"more":[101],"easily":[102],"accessible":[103],"with":[104,180,208],"this":[105],"view":[106],"technology":[108],"offers":[109],"clear":[111],"exciting":[113],"as":[115,141],"motor":[116],"assessment":[117],"by":[118,136],"doctor":[120],"at":[121,124],"patient":[123],"home.":[125],"perpetrator":[127],"send":[129],"directly":[132],"field":[135],"combining":[137],"expertise":[138],"perspective":[140],"from":[142],"therapy":[144],"insight":[145],"into":[146],"application":[148,196],"human":[153],"health,":[154],"especially":[155],"elderly.":[157],"This":[158],"focusing":[160],"safe":[163],"comfortable":[165],"way.":[166],"These":[167],"models":[168],"use":[169,204],"CNN":[170],"LSTM":[172],"classified":[174],"labeling":[175],"landmark":[176],"point":[177],"detection":[178],"results":[179],"high":[181],"performance":[182],"97,3":[183],"accuracy":[184],"average":[185],"range":[190],"30":[191],"FPS.":[192],"So":[193],"heuristic":[195],"system":[197],"recommended":[200],"monitoring":[202],"all":[209],"its":[210],"limitations":[211]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}