{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T11:18:58Z","timestamp":1788261538369,"version":"build-2803163510"},"reference-count":40,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Biomimetics"],"abstract":"<jats:p>Manual soldering requires phase-dependent coordination of posture, hand movement, tool position, and visual attention. We propose a depth-camera framework that estimates the work phase and detects deviations using three-dimensional upper-body and hand features, task-related object positions, and gaze-related approximation features derived from facial orientation and head posture. The system estimates three predefined phases: preparation, active soldering, and cleanup. Windows with insufficient phase confidence are assigned to Uncertain Phase and routed to review rather than treated as deviation labels. In the evaluation, normal trials showed stable process sequences, whereas trials with scripted simulated unsafe-like movements produced local increases in the deviation score and review-required intervals associated with reduced phase-estimation reliability. These findings suggest that the framework may support retrospective safety-related assessment and the identification of process-inconsistent operations in seated manual soldering under controlled laboratory conditions. The bio-inspired contribution is a functional abstraction of phase-dependent perceptual-motor coordination into context-dependent engineering reference patterns and an uncertainty-aware review mechanism.<\/jats:p>","DOI":"10.3390\/biomimetics11090618","type":"journal-article","created":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T10:32:18Z","timestamp":1788258738000},"page":"618","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Process Phase Estimation and Deviation Detection for Manual Soldering Based on Motion Analysis"],"prefix":"10.3390","volume":"11","author":[{"given":"Kyohei","family":"Wakabayashi","sequence":"first","affiliation":[{"name":"Graduate School of Engineering, Oita University, 700 Dannoharu, Oita 870-1192, Japan"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"software","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6306-1976","authenticated-orcid":false,"given":"Tetsuya","family":"Oda","sequence":"additional","affiliation":[{"name":"DX Human Resource Development Foundation Program, Department of Science and Technology, Faculty of Science and Technology, Oita University, 700 Dannoharu, Oita 870-1192, Japan"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"software","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"project-administration","vocabulary":"credit"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"55","DOI":"10.5334\/aogh.3256","article-title":"Ergonomic Design of Manual Assembly Workstation Using Digital Human Modeling","volume":"87","author":"Alipoor","year":"2021","journal-title":"Ann. Glob. Health"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Yang, F., Di, N., Guo, W.-W., Ding, W.-B., Jia, N., Zhang, H., Li, D., Wang, D., Wang, R., and Zhang, D. (2023). The Prevalence and Risk Factors of Work Related Musculoskeletal Disorders among Electronics Manufacturing Workers: A Cross-Sectional Analytical Study in China. BMC Public Health, 23.","DOI":"10.1186\/s12889-022-14952-6"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1016\/S0003-6870(03)00051-6","article-title":"A New Table for Work with a Microscope, a Solution to Ergonomic Problems","volume":"34","author":"Nyberg","year":"2003","journal-title":"Appl. Ergon."},{"key":"ref_4","unstructured":"(2022). Standard for Soldering Process for Space Use (Standard No. JERG-0-039D(E)). Available online: https:\/\/sma.jaxa.jp\/TechDoc\/Docs\/E_JAXA-JERG-0-039D.pdf."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Cao, Z., Simon, T., Wei, S.-E., and Sheikh, Y. (2017). Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), IEEE.","DOI":"10.1109\/CVPR.2017.143"},{"key":"ref_6","unstructured":"Lugaresi, C., Tang, J., Nash, H., McClanahan, C., Uboweja, E., Hays, M., Zhang, F., Chang, C.-L., Yong, M.G., and Lee, J. (2019). MediaPipe: A Framework for Building Perception Pipelines. arXiv."},{"key":"ref_7","unstructured":"Bazarevsky, V., Grishchenko, I., Raveendran, K., Zhu, T., Zhang, F., and Grundmann, M. (2020). BlazePose: On-device Real-Time Body Pose Tracking. arXiv."},{"key":"ref_8","unstructured":"Zhang, F., Bazarevsky, V., Vakunov, A., Tkachenka, A., Sung, G., Chang, C.-L., and Grundmann, M. (2020). MediaPipe Hands: On-device Real-Time Hand Tracking. arXiv."},{"key":"ref_9","unstructured":"Kartynnik, Y., Ablavatski, A., Grishchenko, I., and Grundmann, M. (2019). Real-time Facial Surface Geometry from Monocular Video on Mobile GPUs. arXiv."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/0003-6870(93)90080-S","article-title":"RULA: A Survey Method for the Investigation of Work-Related Upper Limb Disorders","volume":"24","author":"McAtamney","year":"1993","journal-title":"Appl. Ergon."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"103138","DOI":"10.1016\/j.apergo.2020.103138","article-title":"A Novel Vision-Based Real-Time Method for Evaluating Postural Risk Factors Associated with Musculoskeletal Disorders","volume":"87","author":"Li","year":"2020","journal-title":"Appl. Ergon."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"103218","DOI":"10.1016\/j.ergon.2021.103218","article-title":"Development of a Fully Automated RULA Assessment System Based on Computer Vision","volume":"86","author":"Nayak","year":"2021","journal-title":"Int. J. Ind. Ergon."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"103725","DOI":"10.1016\/j.autcon.2021.103725","article-title":"Automated Postural Ergonomic Risk Assessment Using Vision-Based Posture Classification","volume":"128","author":"Seo","year":"2021","journal-title":"Autom. Constr."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"27785","DOI":"10.1038\/s41598-024-79373-4","article-title":"Validation of Computer Vision-Based Ergonomic Risk Assessment Tools for Real Manufacturing Environments","volume":"14","author":"Agostinelli","year":"2024","journal-title":"Sci. Rep."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2139","DOI":"10.1038\/s41598-022-05812-9","article-title":"Automatic Real-Time Occupational Posture Evaluation and Select Corresponding Ergonomic Assessments","volume":"12","author":"Lin","year":"2022","journal-title":"Sci. Rep."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Redmon, J., Divvala, S., Girshick, R., and Farhadi, A. (2016). You Only Look Once: Unified, Real-Time Object Detection. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), IEEE.","DOI":"10.1109\/CVPR.2016.91"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"He, K., Gkioxari, G., Doll\u00e1r, P., and Girshick, R. (2017). Mask R-CNN. Proceedings of the IEEE International Conference on Computer Vision (ICCV), IEEE.","DOI":"10.1109\/ICCV.2017.322"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"925","DOI":"10.1108\/AA-06-2018-078","article-title":"Utilising Low Cost RGB-D Cameras to Track the Real Time Progress of a Manual Assembly Sequence","volume":"40","author":"Oyekan","year":"2020","journal-title":"Assem. Autom."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1016\/j.jmsy.2020.04.018","article-title":"Repetitive Assembly Action Recognition Based on Object Detection and Pose Estimation","volume":"55","author":"Chen","year":"2020","journal-title":"J. Manuf. Syst."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"K\u00e4stner, L., Eversberg, L., Mursa, M., and Lambrecht, J. (2021). Integrative Object and Pose to Task Detection for an Augmented-Reality-Based Human Assistance System Using Neural Networks. 2020 IEEE Eighth International Conference on Communications and Electronics (ICCE), IEEE.","DOI":"10.1109\/ICCE48956.2021.9352121"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Coronado, E., Fukuda, K., Ramirez-Alpizar, I.G., Yamanobe, N., Venture, G., and Harada, K. (2021). Assembly Action Understanding from Fine-Grained Hand Motions, a Multi-camera and Deep Learning Approach. 2021 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE.","DOI":"10.1109\/IROS51168.2021.9636715"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"110527","DOI":"10.1016\/j.cie.2024.110527","article-title":"Deep Learning Based Assembly Process Action Recognition and Progress Prediction Facing Human-Centric Intelligent Manufacturing","volume":"196","author":"Wang","year":"2024","journal-title":"Comput. Ind. Eng."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2215","DOI":"10.1007\/s10845-023-02152-x","article-title":"Fine-Grained Activity Classification in Assembly Based on Multi-Visual Modalities","volume":"35","author":"Chen","year":"2024","journal-title":"J. Intell. Manuf."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"745","DOI":"10.1038\/s41597-022-01843-z","article-title":"The HA4M Dataset: Multi-Modal Monitoring of an Assembly Task for Human Action Recognition in Manufacturing","volume":"9","author":"Cicirelli","year":"2022","journal-title":"Sci. Data"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"B\u00fcsch, L., Koch, J., Schoepflin, D., Schulze, M., and Sch\u00fcppstuhl, T. (2023). Towards Recognition of Human Actions in Collaborative Tasks with Robots: Extending Action Recognition with Tool Recognition Methods. Sensors, 23.","DOI":"10.3390\/s23125718"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1016\/j.jmsy.2024.09.003","article-title":"Digital Ergonomic Assessment to Enhance the Physical Resilience of Human-Centric Manufacturing Systems in Industry 5.0","volume":"77","author":"Tomelleri","year":"2024","journal-title":"J. Manuf. Syst."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"103734","DOI":"10.1016\/j.ergon.2025.103734","article-title":"Validation of Markerless Vision-Based Motion Capture for Ergonomics Risk Assessment","volume":"107","author":"Bonakdar","year":"2025","journal-title":"Int. J. Ind. Ergon."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"104592","DOI":"10.1016\/j.cviu.2025.104592","article-title":"A Vision-Based Framework and Dataset for Human Behavior Understanding in Industrial Assembly Lines","volume":"263","author":"Papoutsakis","year":"2026","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_29","unstructured":"European Cooperation for Space Standardization (2022). ECSS-Q-ST-70-61C: High Reliability Assembly for Surface Mount and Through Hole Connections, ECSS Secretariat. Available online: https:\/\/ecss.nl\/standard\/ecss-q-st-70-61c-high-reliability-assembly-for-surface-mount-and-through-hole-connections-8-april-2022\/."},{"key":"ref_30","unstructured":"IPC (2024). IPC J-STD-001J: Requirements for Soldered Electrical and Electronic Assemblies, IPC."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1060","DOI":"10.1080\/001401399185144","article-title":"Seated Work Postures for Manual, Visual and Combined Tasks","volume":"42","author":"Li","year":"1999","journal-title":"Ergonomics"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1080\/00140130120518","article-title":"The Use of Mirrors during an Assembly Task: A Study of Ergonomics and Productivity","volume":"44","author":"Lutz","year":"2001","journal-title":"Ergonomics"},{"key":"ref_33","first-page":"445","article-title":"An Ergonomic Intervention to Reduce Musculoskeletal Discomfort among Semiconductor Assembly Workers","volume":"54","author":"Aghilinejad","year":"2016","journal-title":"Work"},{"key":"ref_34","first-page":"285","article-title":"A Motion Analysis System for Danger Prediction During Soldering Process","volume":"231","author":"Wakabayashi","year":"2025","journal-title":"Adv. Broad-Band. Wirel. Comput. Commun. Appl."},{"key":"ref_35","first-page":"102","article-title":"A Camera Placement Optimization System for Motion Analysis Considering Posture Changes During Soldering Work","volume":"278","author":"Wakabayashi","year":"2026","journal-title":"Adv. Broad-Band. Wirel. Comput. Commun. Appl."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1007\/978-3-031-26281-4_36","article-title":"A Depth Camera Based Soldering Motion Analysis System for Attention Posture Detection Considering Body Orientation","volume":"161","author":"Toyoshima","year":"2023","journal-title":"Adv. Internet Data Web Technol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"103917","DOI":"10.1016\/j.cag.2024.103917","article-title":"3D Pose Estimation Using Joint-Based Calibration in Distributed RGB-D Camera System","volume":"120","author":"Park","year":"2024","journal-title":"Comput. Graph."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"103631","DOI":"10.1016\/j.net.2025.103631","article-title":"3D Pose Estimation of Workers in Complex Radioactive Environments Using a Single RGB-D Camera","volume":"57","author":"Lee","year":"2025","journal-title":"Nucl. Eng. Technol."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Bonfiglio, A., Tacconi, D., Bongers, R.M., and Farella, E. (2024). Effects of IMU Sensor-to-Segment Calibration on Clinical 3D Elbow Joint Angles Estimation. Front. Bioeng. Biotechnol., 12.","DOI":"10.3389\/fbioe.2024.1385750"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"e48","DOI":"10.1017\/wtc.2025.10026","article-title":"Using a Wearable System Combining Inertial and Force Sensing for Simultaneous Detection of Limb Motion and Grasping Actions in the Workplace","volume":"6","author":"Musso","year":"2025","journal-title":"Wearable Technol."}],"container-title":["Biomimetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2313-7673\/11\/9\/618\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T10:54:57Z","timestamp":1788260097000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2313-7673\/11\/9\/618"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,1]]},"references-count":40,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2026,9]]}},"alternative-id":["biomimetics11090618"],"URL":"https:\/\/doi.org\/10.3390\/biomimetics11090618","relation":{},"ISSN":["2313-7673"],"issn-type":[{"value":"2313-7673","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,1]]}}}