{"id":"https://openalex.org/W4407937743","doi":"https://doi.org/10.1109/thms.2025.3539187","title":"A Single-Camera Method for Estimating Lift Asymmetry Angles Using Deep Learning Computer Vision Algorithms","display_name":"A Single-Camera Method for Estimating Lift Asymmetry Angles Using Deep Learning Computer Vision Algorithms","publication_year":2025,"publication_date":"2025-02-25","ids":{"openalex":"https://openalex.org/W4407937743","doi":"https://doi.org/10.1109/thms.2025.3539187","pmid":"https://pubmed.ncbi.nlm.nih.gov/40160534"},"language":"en","primary_location":{"id":"doi:10.1109/thms.2025.3539187","is_oa":false,"landing_page_url":"https://doi.org/10.1109/thms.2025.3539187","pdf_url":null,"source":{"id":"https://openalex.org/S2476799526","display_name":"IEEE Transactions on Human-Machine Systems","issn_l":"2168-2291","issn":["2168-2291","2168-2305"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Human-Machine Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5024617247","display_name":"Zhengyang Lou","orcid":null},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhengyang Lou","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037864654","display_name":"Zitong Zhan","orcid":null},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zitong Zhan","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108699252","display_name":"Huan Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Huan Xu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100451141","display_name":"Yin Li","orcid":"https://orcid.org/0000-0003-4173-9453"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yin Li","raw_affiliation_strings":["Department of Biostatistics &amp; Medical Informatics and Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI, USA"],"affiliations":[{"raw_affiliation_string":"Department of Biostatistics &amp; Medical Informatics and Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100721274","display_name":"Yu Hen Hu","orcid":"https://orcid.org/0000-0003-3427-0677"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yu Hen Hu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061368037","display_name":"Ming\u2010Lun Lu","orcid":"https://orcid.org/0000-0002-8291-9111"},"institutions":[{"id":"https://openalex.org/I198423848","display_name":"National Institute for Occupational Safety and Health","ror":"https://ror.org/0502a2655","country_code":"US","type":"facility","lineage":["https://openalex.org/I1289490764","https://openalex.org/I1299022934","https://openalex.org/I198423848"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ming-Lun Lu","raw_affiliation_strings":["CDC National Institute for Occupational Safety and Health, Division of Field Studies and Engineering, Cincinnati, OH, USA"],"affiliations":[{"raw_affiliation_string":"CDC National Institute for Occupational Safety and Health, Division of Field Studies and Engineering, Cincinnati, OH, USA","institution_ids":["https://openalex.org/I198423848"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063684855","display_name":"Dwight Werren","orcid":null},"institutions":[{"id":"https://openalex.org/I198423848","display_name":"National Institute for Occupational Safety and Health","ror":"https://ror.org/0502a2655","country_code":"US","type":"facility","lineage":["https://openalex.org/I1289490764","https://openalex.org/I1299022934","https://openalex.org/I198423848"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dwight M. Werren","raw_affiliation_strings":["CDC National Institute for Occupational Safety and Health, Taft Laboratories, Cincinnati, OH, USA"],"affiliations":[{"raw_affiliation_string":"CDC National Institute for Occupational Safety and Health, Taft Laboratories, Cincinnati, OH, USA","institution_ids":["https://openalex.org/I198423848"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062951506","display_name":"Robert G. Radwin","orcid":"https://orcid.org/0000-0002-7973-0641"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Robert G. Radwin","raw_affiliation_strings":["Department of Industrial and Systems Engineering and the Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, USA"],"affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering and the Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5024617247"],"corresponding_institution_ids":["https://openalex.org/I135310074"],"apc_list":null,"apc_paid":null,"fwci":3.8301,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.91854771,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"55","issue":"2","first_page":"309","last_page":"314"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12546","display_name":"Smart Parking Systems Research","score":0.9427000284194946,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T12546","display_name":"Smart Parking Systems Research","score":0.9427000284194946,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/lift","display_name":"Lift (data mining)","score":0.6756042838096619},{"id":"https://openalex.org/keywords/asymmetry","display_name":"Asymmetry","score":0.6383854150772095},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5964686870574951},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5915444493293762},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5438324809074402},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43336617946624756},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.3451305031776428},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.16075649857521057},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06897643208503723}],"concepts":[{"id":"https://openalex.org/C139002025","wikidata":"https://www.wikidata.org/wiki/Q3001212","display_name":"Lift (data mining)","level":2,"score":0.6756042838096619},{"id":"https://openalex.org/C38976095","wikidata":"https://www.wikidata.org/wiki/Q752641","display_name":"Asymmetry","level":2,"score":0.6383854150772095},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5964686870574951},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5915444493293762},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5438324809074402},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43336617946624756},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.3451305031776428},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.16075649857521057},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06897643208503723},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/thms.2025.3539187","is_oa":false,"landing_page_url":"https://doi.org/10.1109/thms.2025.3539187","pdf_url":null,"source":{"id":"https://openalex.org/S2476799526","display_name":"IEEE Transactions on Human-Machine Systems","issn_l":"2168-2291","issn":["2168-2291","2168-2305"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Human-Machine Systems","raw_type":"journal-article"},{"id":"pmid:40160534","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40160534","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on human-machine systems","raw_type":null},{"id":"pmh:oai:europepmc.org:10768635","is_oa":false,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11951292","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7063437407","display_name":null,"funder_award_id":"R01OH011024","funder_id":"https://openalex.org/F4320332162","funder_display_name":"Centers for Disease Control and Prevention"},{"id":"https://openalex.org/G8673860898","display_name":null,"funder_award_id":"R01OH011024","funder_id":"https://openalex.org/F4320337382","funder_display_name":"National Institute for Occupational Safety and Health"}],"funders":[{"id":"https://openalex.org/F4320332162","display_name":"Centers for Disease Control and Prevention","ror":"https://ror.org/042twtr12"},{"id":"https://openalex.org/F4320337382","display_name":"National Institute for Occupational Safety and Health","ror":"https://ror.org/0502a2655"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1967785790","https://openalex.org/W2041757785","https://openalex.org/W2080381589","https://openalex.org/W2101032778","https://openalex.org/W2123141568","https://openalex.org/W2131625981","https://openalex.org/W2159620389","https://openalex.org/W2169738563","https://openalex.org/W2294661077","https://openalex.org/W2335645555","https://openalex.org/W2496938104","https://openalex.org/W2565104410","https://openalex.org/W2783860278","https://openalex.org/W2888880367","https://openalex.org/W2889665152","https://openalex.org/W2893365938","https://openalex.org/W2905147676","https://openalex.org/W2907268465","https://openalex.org/W2916798096","https://openalex.org/W2945575082","https://openalex.org/W2962896489","https://openalex.org/W2962936462","https://openalex.org/W2963150697","https://openalex.org/W2991217393","https://openalex.org/W2991247554","https://openalex.org/W2991583223","https://openalex.org/W2998027150","https://openalex.org/W3016980072","https://openalex.org/W3034581612","https://openalex.org/W4391377600","https://openalex.org/W6729304362","https://openalex.org/W6747620207","https://openalex.org/W6750378959","https://openalex.org/W6767176642","https://openalex.org/W6773998060","https://openalex.org/W6780031573","https://openalex.org/W6803376173"],"related_works":["https://openalex.org/W2051487156","https://openalex.org/W1980563100","https://openalex.org/W1644661642","https://openalex.org/W4297670902","https://openalex.org/W2035154026","https://openalex.org/W2065779551","https://openalex.org/W2050217822","https://openalex.org/W3102935140","https://openalex.org/W2073681303","https://openalex.org/W2001403916"],"abstract_inverted_index":{"A":[0,24,78],"computer":[1],"vision":[2],"(CV)":[3],"method":[4,68],"to":[5,35,40,116],"automatically":[6],"measure":[7],"the":[8,66,96,112,120,142],"revised":[9],"NIOSH":[10],"lifting":[11],"equation":[12],"asymmetry":[13],"angle":[14],"(<i>A</i>)":[15],"from":[16,72],"a":[17,73,91],"single":[18],"camera":[19,61],"is":[20],"described":[21],"and":[22,58,90],"tested.":[23],"laboratory":[25],"study":[26],"involving":[27],"ten":[28],"participants":[29],"performing":[30],"various":[31],"lifts":[32],"was":[33,128,151],"used":[34],"estimate":[36],"<i>A</i>":[37],"in":[38,60,63,86],"comparison":[39],"ground":[41],"truth":[42],"joint":[43],"coordinates":[44,71,85],"obtained":[45],"using":[46,119],"3-D":[47,92],"motion":[48],"capture":[49],"(MoCap).":[50],"To":[51],"address":[52],"challenges,":[53],"such":[54],"as":[55],"obstructed":[56],"views":[57],"limitations":[59],"placement":[62],"real-world":[64],"scenarios,":[65],"CV":[67,113,143],"utilized":[69],"video-derived":[70],"selected":[74],"set":[75],"of":[76,98,123,141],"landmarks.":[77],"2-D":[79,100],"pose":[80],"estimator":[81],"(HR-Net)":[82],"detected":[83],"landmark":[84,101,149],"each":[87,99],"video":[88],"frame,":[89],"algorithm":[93],"(VideoPose3D)":[94],"estimated":[95],"depth":[97],"by":[102],"analyzing":[103],"its":[104],"trajectories.":[105],"The":[106,136],"mean":[107,137],"absolute":[108,138],"precision":[109],"error":[110,140],"for":[111,125],"method,":[114,144],"compared":[115,145],"MoCap":[117,148],"measurements":[118],"same":[121],"subset":[122],"landmarks":[124],"estimating":[126],"<i>A</i>,":[127],"6.25\u00b0":[129],"(SD":[130,153],"=":[131,134,154,157],"10.19\u00b0,":[132],"N":[133],"360).":[135,158],"accuracy":[139],"against":[146],"conventional":[147],"markers":[150],"9.45\u00b0":[152],"14.01\u00b0,":[155],"<i>N</i>":[156]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
