{"id":"https://openalex.org/W4406208647","doi":"https://doi.org/10.1109/icarcv63323.2024.10821696","title":"A Machine Learning-Based Fatigue Extraction Method Using Human Manipulation Video Data in Smart Manufacturing","display_name":"A Machine Learning-Based Fatigue Extraction Method Using Human Manipulation Video Data in Smart Manufacturing","publication_year":2024,"publication_date":"2024-12-12","ids":{"openalex":"https://openalex.org/W4406208647","doi":"https://doi.org/10.1109/icarcv63323.2024.10821696"},"language":"en","primary_location":{"id":"doi:10.1109/icarcv63323.2024.10821696","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarcv63323.2024.10821696","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 18th International Conference on Control, Automation, Robotics and Vision (ICARCV)","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/A5025397133","display_name":"Jiarong Yao","orcid":"https://orcid.org/0000-0003-3058-189X"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Jiarong Yao","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Nanyang Technological University,Singapore,639798"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University,Singapore,639798","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Nabeel Muhammad","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Nabeel Muhammad","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Nanyang Technological University,Singapore,639798"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University,Singapore,639798","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062188808","display_name":"Chongshan He","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Chongshan He","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Nanyang Technological University,Singapore,639798"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University,Singapore,639798","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104258174","display_name":"Kaixu Li","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Kaixu Li","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Nanyang Technological University,Singapore,639798"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University,Singapore,639798","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046844818","display_name":"Rong Su","orcid":"https://orcid.org/0000-0003-3448-0586"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Rong Su","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Nanyang Technological University,Centre for Advanced Robotics Technology Innovation (CARTIN),Singapore,639798"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University,Centre for Advanced Robotics Technology Innovation (CARTIN),Singapore,639798","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5025397133"],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.36649215,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"524","last_page":"529"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.8457000255584717,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.8457000255584717,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T12006","display_name":"Ergonomics and Musculoskeletal Disorders","score":0.8062000274658203,"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/computer-science","display_name":"Computer science","score":0.7055305242538452},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.5803406238555908},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5428509712219238},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4533507227897644},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4348231256008148},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4226561188697815},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3309060335159302}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7055305242538452},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.5803406238555908},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5428509712219238},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4533507227897644},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4348231256008148},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4226561188697815},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3309060335159302},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icarcv63323.2024.10821696","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarcv63323.2024.10821696","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 18th International Conference on Control, Automation, Robotics and Vision (ICARCV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.49000000953674316}],"awards":[{"id":"https://openalex.org/G8529416951","display_name":null,"funder_award_id":"I2001E0067","funder_id":"https://openalex.org/F4320320696","funder_display_name":"Agency for Science, Technology and Research"}],"funders":[{"id":"https://openalex.org/F4320320696","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1506547065","https://openalex.org/W2047433445","https://openalex.org/W2568343704","https://openalex.org/W2730676472","https://openalex.org/W2909320737","https://openalex.org/W2916006248","https://openalex.org/W2962730651","https://openalex.org/W3003310656","https://openalex.org/W3023750556","https://openalex.org/W3111200617","https://openalex.org/W4313275337","https://openalex.org/W4328007756","https://openalex.org/W4362591270","https://openalex.org/W4389945770"],"related_works":["https://openalex.org/W2377297411","https://openalex.org/W2961085424","https://openalex.org/W3148217948","https://openalex.org/W4224009465","https://openalex.org/W2375788636","https://openalex.org/W2358561207","https://openalex.org/W4306674287","https://openalex.org/W2975617233","https://openalex.org/W4286629047","https://openalex.org/W2388704129"],"abstract_inverted_index":{"As":[0],"an":[1,152],"important":[2],"part":[3],"in":[4],"smart":[5,103],"manufacturing":[6,104],"under":[7,102],"Industry":[8],"4.0":[9],"era,":[10],"human-robot":[11],"collaboration":[12],"(HRC)":[13],"features":[14],"the":[15,24,59,96,112,147,159,163,169,179,196,218,222,233,240,243],"interaction":[16],"between":[17],"human":[18,27,37,71,83,100,107,182],"operators":[19,101],"and":[20,46,53,61,135,167,211,226],"machines,":[21],"which":[22],"makes":[23],"research":[25],"of":[26,55,63,91,99,181,187,220,242],"fatigue":[28,38,72,183],"come":[29],"into":[30],"sight.":[31],"However,":[32],"most":[33],"existing":[34],"studies":[35],"on":[36,76,82],"or":[39],"efficiency":[40],"detection":[41,52],"are":[42,175,214],"realized":[43],"using":[44,114,137,162],"detectors":[45],"models":[47],"from":[48,111],"bioelectronics,":[49],"whose":[50],"intrusive":[51],"decoding":[54],"electromyographic":[56],"signal":[57],"limits":[58],"generality":[60],"applicability":[62],"such":[64],"methods.":[65],"Therefore,":[66],"this":[67,145],"study":[68],"proposes":[69],"a":[70,115,122,138],"extraction":[73,119],"method":[74],"based":[75],"video":[77,89,113],"data.":[78],"A":[79],"new":[80],"dataset":[81],"manipulation":[84],"is":[85,129,189],"established":[86],"by":[87],"collecting":[88],"data":[90,109,174],"assembly":[92,153],"operations":[93],"to":[94,150,177,216,232],"simulate":[95],"working":[97,132,192],"status":[98,133,193],"environment.":[105],"With":[106],"skeletal":[108],"extracted":[110,157,223],"machine":[116],"learning-based":[117],"pose":[118],"tool,":[120],"MediaPipe,":[121],"spatiotemporal":[123],"analysis":[124],"for":[125,131,191,195],"critical":[126],"skeleton":[127],"points":[128],"implemented":[130],"categorization":[134],"learning":[136],"stochastic":[139],"gradient":[140],"descent":[141],"(SGD)":[142],"classifier.":[143],"In":[144],"way,":[146],"duration":[148],"taken":[149],"complete":[151],"task":[154],"can":[155],"be":[156],"as":[158,230],"operation":[160,171,224],"time":[161,172,225],"trained":[164],"SGD":[165],"classifier,":[166],"thus":[168],"time-varying":[170,228],"series":[173],"obtained":[176,190],"show":[178],"trend":[180],"level.":[184],"An":[185],"accuracy":[186,219],"98.3%":[188],"identification":[194],"dataset.":[197],"Several":[198],"quantitative":[199],"indicators":[200],"like":[201],"pearson":[202],"correlation,":[203],"R-squared":[204],"value,":[205],"root":[206],"mean":[207],"squared":[208],"error":[209],"(RMSE),":[210],"Fr\u00e9chet":[212],"Distance,":[213],"used":[215],"evaluate":[217],"both":[221],"its":[227],"curve":[229],"compared":[231],"ground":[234],"truth,":[235],"with":[236],"satisfactory":[237],"results":[238],"showing":[239],"effectiveness":[241],"proposed":[244],"method.":[245]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}