{"id":"https://openalex.org/W7154356265","doi":"https://doi.org/10.1142/s0219519426500272","title":"FROM KEYPOINTS TO ACTIONS: REAL-TIME MOTION ANALYSIS USING MOVENET AND LIGHTWEIGHT Conv1D NETWORKS","display_name":"FROM KEYPOINTS TO ACTIONS: REAL-TIME MOTION ANALYSIS USING MOVENET AND LIGHTWEIGHT Conv1D NETWORKS","publication_year":2026,"publication_date":"2026-04-14","ids":{"openalex":"https://openalex.org/W7154356265","doi":"https://doi.org/10.1142/s0219519426500272"},"language":"en","primary_location":{"id":"doi:10.1142/s0219519426500272","doi":"https://doi.org/10.1142/s0219519426500272","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219519426500272","pdf_url":null,"source":{"id":"https://openalex.org/S133264478","display_name":"Journal of Mechanics in Medicine and Biology","issn_l":"0219-5194","issn":["0219-5194","1793-6810"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","jufo-1","norway-1","poland-40","russia-white-list-4"],"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Mechanics in Medicine and Biology","raw_type":"journal-article"},"volume":null,"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/A5021625198","display_name":"Jui-Liang Hsu","orcid":"https://orcid.org/0009-0002-8926-1532","observed_orcids":["https://orcid.org/0009-0002-8926-1532"]},"institutions":[{"id":"https://openalex.org/I91951123","display_name":"Cheng Shiu University","ror":"https://ror.org/011bdtx65","country_code":"TW","type":"education","lineage":["https://openalex.org/I91951123"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"JUI-LIANG HSU","raw_affiliation_strings":["Department of Leisure and Sports Management, Cheng Shiu University, Kaohsiung 833, Taiwan"],"raw_orcid":"https://orcid.org/0009-0002-8926-1532","affiliations":[{"raw_affiliation_string":"Department of Leisure and Sports Management, Cheng Shiu University, Kaohsiung 833, Taiwan","institution_ids":["https://openalex.org/I91951123"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133575272","display_name":"Keng-Hsi Lin","orcid":"https://orcid.org/0009-0000-3467-3471","observed_orcids":["https://orcid.org/0009-0000-3467-3471"]},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"KENG-HSI LIN","raw_affiliation_strings":["Department of Engineering Science, National Cheng Kung University, Tainan 701, Taiwan"],"raw_orcid":"https://orcid.org/0009-0000-3467-3471","affiliations":[{"raw_affiliation_string":"Department of Engineering Science, National Cheng Kung University, Tainan 701, Taiwan","institution_ids":["https://openalex.org/I91807558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108882305","display_name":"Yu\u2010Hsuan Chiang","orcid":"https://orcid.org/0009-0009-9233-7826","observed_orcids":["https://orcid.org/0009-0009-9233-7826"]},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"YU-HSUAN CHIANG","raw_affiliation_strings":["Department of Engineering Science, National Cheng Kung University, Tainan 701, Taiwan"],"raw_orcid":"https://orcid.org/0009-0009-9233-7826","affiliations":[{"raw_affiliation_string":"Department of Engineering Science, National Cheng Kung University, Tainan 701, Taiwan","institution_ids":["https://openalex.org/I91807558"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038663636","display_name":"Mu\u2010Yen Chen","orcid":"https://orcid.org/0000-0002-3945-4363","observed_orcids":["https://orcid.org/0000-0002-3945-4363"]},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"MU-YEN CHEN","raw_affiliation_strings":["Department of Engineering Science, National Cheng Kung University, Tainan 701, Taiwan"],"raw_orcid":"https://orcid.org/0000-0002-3945-4363","affiliations":[{"raw_affiliation_string":"Department of Engineering Science, National Cheng Kung University, Tainan 701, Taiwan","institution_ids":["https://openalex.org/I91807558"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22535759,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9994999766349792,"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":0.9994999766349792,"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":0.00019999999494757503,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":9.999999747378752e-05,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/motion-analysis","display_name":"motion analysis","score":0.6940000057220459},{"id":"https://openalex.org/keywords/human-pose-estimation","display_name":"human pose estimation","score":0.609000027179718},{"id":"https://openalex.org/keywords/movenet","display_name":"MoveNet","score":0.8999999761581421},{"id":"https://openalex.org/keywords/human-action-recognition","display_name":"human action recognition","score":0.5299999713897705},{"id":"https://openalex.org/keywords/sports-performance-evaluation","display_name":"sports performance evaluation","score":0.7570000290870667},{"id":"https://openalex.org/keywords/workplace-safety-monitoring","display_name":"workplace safety monitoring","score":0.9229999780654907}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.713699996471405},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6248000264167786},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.602400004863739},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5849000215530396},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5321999788284302},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.4564000070095062},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44209998846054077},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.3977999985218048},{"id":"https://openalex.org/C3018824978","wikidata":"https://www.wikidata.org/wiki/Q2894891","display_name":"Error analysis","level":2,"score":0.3450999855995178},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.3443000018596649},{"id":"https://openalex.org/C2777036941","wikidata":"https://www.wikidata.org/wiki/Q6917771","display_name":"Motion analysis","level":2,"score":0.34200000762939453},{"id":"https://openalex.org/C2986578859","wikidata":"https://www.wikidata.org/wiki/Q657632","display_name":"Human motion","level":3,"score":0.3149999976158142},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.2973000109195709},{"id":"https://openalex.org/C169806903","wikidata":"https://www.wikidata.org/wiki/Q5937752","display_name":"Human error","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2786000072956085},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2702000141143799},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.25999999046325684}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0219519426500272","doi":"https://doi.org/10.1142/s0219519426500272","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219519426500272","pdf_url":null,"source":{"id":"https://openalex.org/S133264478","display_name":"Journal of Mechanics in Medicine and Biology","issn_l":"0219-5194","issn":["0219-5194","1793-6810"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","jufo-1","norway-1","poland-40","russia-white-list-4"],"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Mechanics in Medicine and Biology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G7476826901","display_name":"Applying the Multi-Model Artificial Intelligence Integrated with Large Language Model for Prediction and Classification of Classroom Behavior","funder_award_id":"NSTC114-2622-H006-006","funder_id":"https://openalex.org/F2461203286","funder_display_name":"National Science and Technology Council"},{"id":"https://openalex.org/G7666646145","display_name":"The Application of Generative Ai and Large Language Models in Engineering Education - Assisting Students in Flipped Learning System Construction, Learning Styles and Learning Effectiveness of Chatgpt","funder_award_id":"NSTC113-2410-H006-083-MY3","funder_id":"https://openalex.org/F2461203286","funder_display_name":"National Science and Technology Council"}],"funders":[{"id":"https://openalex.org/F2461203286","display_name":"National Science and Technology Council","ror":"https://ror.org/02kv4zf79"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2096733369","https://openalex.org/W2147815065","https://openalex.org/W2257979135","https://openalex.org/W2520774990","https://openalex.org/W2559085405","https://openalex.org/W2565639579","https://openalex.org/W2944779197","https://openalex.org/W2962730651","https://openalex.org/W2963163009","https://openalex.org/W2963744743","https://openalex.org/W3110770815","https://openalex.org/W3154050921","https://openalex.org/W4292972976","https://openalex.org/W4319999780","https://openalex.org/W4391814420","https://openalex.org/W4399883454"],"related_works":[],"abstract_inverted_index":{"Motion":[0],"analysis":[1],"provides":[2],"insight":[3],"into":[4],"a":[5,31,83,109,118],"subject\u2019s":[6],"physical":[7],"condition":[8],"or":[9,23],"activity":[10],"status":[11],"and":[12,117,145,158],"can":[13],"help":[14],"prevent":[15],"hazardous":[16],"movements,":[17],"reduce":[18],"the":[19,44,101],"risk":[20],"of":[21,46,52,112,121,128],"accidents,":[22],"support":[24],"sports":[25,154],"performance":[26],"evaluation.":[27],"This":[28],"study":[29],"adopts":[30],"computer":[32],"vision-based":[33],"approach":[34],"combined":[35],"with":[36,114,123],"deep":[37],"neural":[38,85],"networks":[39],"for":[40,87,150],"motion":[41],"classification,":[42],"avoiding":[43],"limitations":[45],"wearable":[47],"sensors.":[48],"The":[49,66,126,139],"dataset":[50],"consists":[51],"publicly":[53],"available":[54],"fitness":[55],"instructional":[56],"videos,":[57],"from":[58],"which":[59,78],"23":[60],"decomposed":[61],"actions":[62],"were":[63],"manually":[64],"annotated.":[65],"proposed":[67,140],"two-stage":[68],"model":[69,107,141],"uses":[70],"MoveNet":[71,102],"to":[72,82,93],"detect":[73],"17":[74],"human":[75],"joint":[76],"coordinates,":[77],"are":[79],"then":[80],"passed":[81],"Conv1D":[84,106],"network":[86],"classification.":[88],"Triplet-Center":[89,129],"Loss":[90,130],"is":[91],"applied":[92],"enhance":[94],"class":[95,134],"separation.":[96],"Experimental":[97],"results":[98],"show":[99],"that":[100],"[Formula:":[103],"see":[104],"text]":[105],"achieved":[108],"training":[110],"error":[111,120],"0.2":[113],"100%":[115],"accuracy":[116],"test":[119],"0.62":[122],"92%":[124],"accuracy.":[125],"use":[127],"resulted":[131],"in":[132,136,153],"well-separated":[133],"clusters":[135],"t-SNE":[137],"visualizations.":[138],"demonstrates":[142],"high":[143],"precision":[144],"efficiency,":[146],"making":[147],"it":[148],"suitable":[149],"future":[151],"applications":[152],"analytics,":[155],"action":[156],"recognition,":[157],"workplace":[159],"safety":[160],"monitoring.":[161]},"counts_by_year":[],"updated_date":"2026-10-14T16:39:01.820549","created_date":"2026-04-15T00:00:00"}