{"id":"https://openalex.org/W4214700230","doi":"https://doi.org/10.1109/imcom53663.2022.9721801","title":"Predict joint angle of body parts based on sequence pattern recognition","display_name":"Predict joint angle of body parts based on sequence pattern recognition","publication_year":2022,"publication_date":"2022-01-03","ids":{"openalex":"https://openalex.org/W4214700230","doi":"https://doi.org/10.1109/imcom53663.2022.9721801"},"language":"en","primary_location":{"id":"doi:10.1109/imcom53663.2022.9721801","is_oa":false,"landing_page_url":"https://doi.org/10.1109/imcom53663.2022.9721801","pdf_url":null,"source":{"id":"https://openalex.org/S4363608555","display_name":"2022 16th International Conference on Ubiquitous Information Management and Communication (IMCOM)","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 16th International Conference on Ubiquitous Information Management and Communication (IMCOM)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2405.17369","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048335607","display_name":"Amin Ahmadi Kasani","orcid":null},"institutions":[{"id":"https://openalex.org/I23946033","display_name":"University of Tehran","ror":"https://ror.org/05vf56z40","country_code":"IR","type":"education","lineage":["https://openalex.org/I23946033"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Amin Ahmadi Kasani","raw_affiliation_strings":["University of Tehran,College of Science,Department of Mathematics, Statistics and Computer Science,Tehran,Iran"],"affiliations":[{"raw_affiliation_string":"University of Tehran,College of Science,Department of Mathematics, Statistics and Computer Science,Tehran,Iran","institution_ids":["https://openalex.org/I23946033"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072704310","display_name":"Hedieh Sajedi","orcid":"https://orcid.org/0000-0003-4782-9222"},"institutions":[{"id":"https://openalex.org/I23946033","display_name":"University of Tehran","ror":"https://ror.org/05vf56z40","country_code":"IR","type":"education","lineage":["https://openalex.org/I23946033"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Hedieh Sajedi","raw_affiliation_strings":["University of Tehran,College of Science,Department of Mathematics, Statistics and Computer Science,Tehran,Iran"],"affiliations":[{"raw_affiliation_string":"University of Tehran,College of Science,Department of Mathematics, Statistics and Computer Science,Tehran,Iran","institution_ids":["https://openalex.org/I23946033"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5048335607"],"corresponding_institution_ids":["https://openalex.org/I23946033"],"apc_list":null,"apc_paid":null,"fwci":0.1065,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.16037188,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"149","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.996399998664856,"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"}},"topics":[{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.996399998664856,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9847999811172485,"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/T12006","display_name":"Ergonomics and Musculoskeletal Disorders","score":0.9817000031471252,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.778708815574646},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.748099684715271},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7140652537345886},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6840509176254272},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5691173076629639},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5125641822814941},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.44139811396598816},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.41619938611984253},{"id":"https://openalex.org/keywords/viewpoints","display_name":"Viewpoints","score":0.4131864905357361},{"id":"https://openalex.org/keywords/human-body","display_name":"Human body","score":0.41277700662612915},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34604668617248535},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20077824592590332},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13121289014816284},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08146488666534424}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.778708815574646},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.748099684715271},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7140652537345886},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6840509176254272},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5691173076629639},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5125641822814941},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.44139811396598816},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.41619938611984253},{"id":"https://openalex.org/C2776035091","wikidata":"https://www.wikidata.org/wiki/Q7928819","display_name":"Viewpoints","level":2,"score":0.4131864905357361},{"id":"https://openalex.org/C193293595","wikidata":"https://www.wikidata.org/wiki/Q23852","display_name":"Human body","level":2,"score":0.41277700662612915},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34604668617248535},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20077824592590332},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13121289014816284},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08146488666534424},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/imcom53663.2022.9721801","is_oa":false,"landing_page_url":"https://doi.org/10.1109/imcom53663.2022.9721801","pdf_url":null,"source":{"id":"https://openalex.org/S4363608555","display_name":"2022 16th International Conference on Ubiquitous Information Management and Communication (IMCOM)","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 16th International Conference on Ubiquitous Information Management and Communication (IMCOM)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2405.17369","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2405.17369","pdf_url":"https://arxiv.org/pdf/2405.17369","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2405.17369","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2405.17369","pdf_url":"https://arxiv.org/pdf/2405.17369","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4214700230.pdf"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2039240409","https://openalex.org/W2064675550","https://openalex.org/W2271840356","https://openalex.org/W2559085405","https://openalex.org/W2981092462","https://openalex.org/W2990719156","https://openalex.org/W3033755024","https://openalex.org/W3082986793","https://openalex.org/W3086816133","https://openalex.org/W3165653836","https://openalex.org/W3169599625","https://openalex.org/W3195607703","https://openalex.org/W4394363419","https://openalex.org/W6631190155","https://openalex.org/W6694517276"],"related_works":["https://openalex.org/W2385368906","https://openalex.org/W2902924992","https://openalex.org/W2626642044","https://openalex.org/W2619807045","https://openalex.org/W2388758053","https://openalex.org/W93537448","https://openalex.org/W2949734191","https://openalex.org/W2017333877","https://openalex.org/W2048332520","https://openalex.org/W4233821346"],"abstract_inverted_index":{"The":[0],"way":[1],"organs":[2],"are":[3,44,94,104,163],"positioned":[4],"and":[5,13,32,100,128,194,217],"moved":[6],"in":[7,35,41,46,58,77,97],"the":[8,27,36,39,42,52,59,74,87,98,167,177,181,185,196,206,225],"workplace":[9],"can":[10],"cause":[11],"pain":[12],"physical":[14],"harm.":[15],"Therefore,":[16,111],"ergonomists":[17],"use":[18],"ergonomic":[19],"risk":[20],"assessments":[21],"based":[22,140],"on":[23,141,224],"visual":[24],"observation":[25],"of":[26,51,62,89,119,187,215,222],"workplace,":[28],"or":[29,69,150],"review":[30],"pictures":[31],"videos":[33],"taken":[34],"workplace.":[37],"Sometimes":[38],"workers":[40],"photos":[43,131],"not":[45,56,95,105,164],"perfect":[47],"condition.":[48],"Some":[49],"parts":[50,91,162,193],"workers'":[53],"bodies":[54],"may":[55],"be":[57,65],"camera's":[60],"field":[61],"view,":[63],"could":[64,175],"obscured":[66],"by":[67,70,179],"objects,":[68],"self-occlusion,":[71],"this":[72,109],"is":[73,83,170],"main":[75],"problem":[76],"2D":[78],"human":[79,122,130,151],"posture":[80],"recognition.":[81],"It":[82],"difficult":[84],"to":[85],"predict":[86],"position":[88],"body":[90,161,192],"when":[92],"they":[93],"visible":[96],"image,":[99],"geometric":[101],"mathematical":[102],"methods":[103],"entirely":[106],"suitable":[107],"for":[108,125,146],"purpose.":[110],"we":[112,137,174,208],"created":[113,154],"a":[114,120,142,201],"dataset":[115],"with":[116,200],"artificial":[117],"images":[118,158,183],"3D":[121,148],"model,":[123],"specifically":[124],"painful":[126],"postures,":[127],"real":[129],"from":[132],"different":[133],"viewpoints.":[134],"Each":[135],"image":[136],"captured":[138],"was":[139],"predefined":[143,191],"joint":[144,168,188,198],"angle":[145,169,199],"each":[147],"model":[149],"model.":[152],"We":[153],"various":[155],"images,":[156],"including":[157],"where":[159],"some":[160],"visible.":[165],"Nevertheless,":[166],"estimated":[171],"beforehand,":[172],"so":[173],"study":[176],"case":[178],"converting":[180],"input":[182],"into":[184],"sequence":[186],"connections":[189],"between":[190],"extracting":[195],"desired":[197],"convolutional":[202],"neural":[203],"network.":[204],"In":[205],"end,":[207],"obtained":[209],"root":[210],"mean":[211,218],"square":[212],"error":[213,220],"(RMSE)":[214],"12.89":[216],"absolute":[219],"(MAE)":[221],"4.7":[223],"test":[226],"dataset.":[227]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
