{"title":"Deep learning-based improvement of joint angle accuracy for uncalibrated multi-view markerless three-dimensional motion capture.","authors":"Taeu Kim, Myung-Chul Jung, Seung-Min Mo","doi":"10.1080/00140139.2026.2718967","DOIUrl":null,"url":null,"abstract":"<p><p>This study aimed to improve and validate the accuracy of joint angles estimated using a mixture of uncalibrated cameras (MUC), an uncalibrated multi-view markerless three-dimensional motion capture system, through bidirectional long short-term memory (BiLSTM) based correction. Twelve male participants performed bricklaying, assembly, and parcel loading while marker-based and multi-view markerless motion capture data were recorded simultaneously. MUC-derived joint angles were corrected using a BiLSTM model trained against marker-based reference values. Representative RMSE reductions were 48.9° to 25.0° for shoulder abduction-adduction in bricklaying, 11.3° to 5.8° for elbow flexion in assembly, and RMSE from 40.0° to 16.7° for knee flexion in parcel loading. Pearson's correlation and ICC improved for several motions, while Bland-Altman analysis showed reduced fixed and proportional bias and narrower limits of agreement in selected motions. These findings support BiLSTM-based correction for industrial ergonomic assessment.</p>","PeriodicalId":50503,"journal":{"name":"Ergonomics","volume":" ","pages":"1-27"},"PeriodicalIF":2.8000,"publicationDate":"2026-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ergonomics","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/00140139.2026.2718967","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 0
Abstract
This study aimed to improve and validate the accuracy of joint angles estimated using a mixture of uncalibrated cameras (MUC), an uncalibrated multi-view markerless three-dimensional motion capture system, through bidirectional long short-term memory (BiLSTM) based correction. Twelve male participants performed bricklaying, assembly, and parcel loading while marker-based and multi-view markerless motion capture data were recorded simultaneously. MUC-derived joint angles were corrected using a BiLSTM model trained against marker-based reference values. Representative RMSE reductions were 48.9° to 25.0° for shoulder abduction-adduction in bricklaying, 11.3° to 5.8° for elbow flexion in assembly, and RMSE from 40.0° to 16.7° for knee flexion in parcel loading. Pearson's correlation and ICC improved for several motions, while Bland-Altman analysis showed reduced fixed and proportional bias and narrower limits of agreement in selected motions. These findings support BiLSTM-based correction for industrial ergonomic assessment.
期刊介绍：
Ergonomics, also known as human factors, is the scientific discipline that seeks to understand and improve human interactions with products, equipment, environments and systems. Drawing upon human biology, psychology, engineering and design, Ergonomics aims to develop and apply knowledge and techniques to optimise system performance, whilst protecting the health, safety and well-being of individuals involved. The attention of ergonomics extends across work, leisure and other aspects of our daily lives.
The journal Ergonomics is an international refereed publication, with a 60 year tradition of disseminating high quality research. Original submissions, both theoretical and applied, are invited from across the subject, including physical, cognitive, organisational and environmental ergonomics. Papers reporting the findings of research from cognate disciplines are also welcome, where these contribute to understanding equipment, tasks, jobs, systems and environments and the corresponding needs, abilities and limitations of people.
All published research articles in this journal have undergone rigorous peer review, based on initial editor screening and anonymous refereeing by independent expert referees.
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