{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,5]],"date-time":"2026-11-05T03:19:38Z","timestamp":1793848778574,"version":"4.6.1"},"reference-count":44,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2022,11,17]],"date-time":"2022-11-17T00:00:00Z","timestamp":1668643200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Ministry of Trade, Industry, and Energy (MOTIE) and the Korea Institute for Advancement of Technology (KIAT)","award":["P0022316"],"award-info":[{"award-number":["P0022316"]}]},{"name":"the Ministry of Trade, Industry, and Energy (MOTIE) and the Korea Institute for Advancement of Technology (KIAT)","award":["NRF-2021R1F1A1060244"],"award-info":[{"award-number":["NRF-2021R1F1A1060244"]}]},{"name":"the Ministry of Trade, Industry, and Energy (MOTIE) and the Korea Institute for Advancement of Technology (KIAT)","award":["NRF-2021R1F1A1047577"],"award-info":[{"award-number":["NRF-2021R1F1A1047577"]}]},{"name":"Ministry of Science and ICT of the Republic of Korea and the National Research Foundation of Korea","award":["P0022316"],"award-info":[{"award-number":["P0022316"]}]},{"name":"Ministry of Science and ICT of the Republic of Korea and the National Research Foundation of Korea","award":["NRF-2021R1F1A1060244"],"award-info":[{"award-number":["NRF-2021R1F1A1060244"]}]},{"name":"Ministry of Science and ICT of the Republic of Korea and the National Research Foundation of Korea","award":["NRF-2021R1F1A1047577"],"award-info":[{"award-number":["NRF-2021R1F1A1047577"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Industries need a mechanism to monitor the workers\u2019 safety and to prevent Work-related Musculoskeletal Disorders (WMSDs). The development of ergonomics assessment tools helps the industry evaluate workplace design and worker posture. Many studies proposed the automated ergonomics assessment method to replace the manual; however, it only focused on calculating body angle and assessing the wrist section manually. This study aims to (a) propose a wrist kinematics measurement based on unobtrusive sensors, (b) detect potential WMSDs related to wrist posture, and (c) compare the wrist posture of subjects while performing assembly tasks to achieve a comprehensive and personalized ergonomic assessment. The wrist posture measurement is combined with the body posture measurement to provide a comprehensive ergonomics assessment based on RULA. Data were collected from subjects who performed the assembly process to evaluate our method. We compared the risk score assessed by the ergonomist and the risk score generated by our method. All body segments achieved more than an 80% similarity score, enhancing the scores for wrist position and wrist twist by 6.8% and 0.3%, respectively. A hypothesis analysis was conducted to evaluate the difference across the subjects. The results indicate that every subject performs tasks differently and has different potential risks regarding wrist posture.<\/jats:p>","DOI":"10.3390\/s22228898","type":"journal-article","created":{"date-parts":[[2022,11,18]],"date-time":"2022-11-18T06:11:34Z","timestamp":1668751894000},"page":"8898","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Sensor-Based Motion Tracking System Evaluation for RULA in Assembly Task"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8070-3210","authenticated-orcid":false,"given":"Wenny Franciska","family":"Senjaya","sequence":"first","affiliation":[{"name":"Department of Industrial and Management Engineering, Hankuk University of Foreign Studies, Yongin 17035, Republic of Korea"},{"name":"Faculty of Information Technology, Maranatha Christian University, Bandung 40164, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bernardo Nugroho","family":"Yahya","sequence":"additional","affiliation":[{"name":"Department of Industrial and Management Engineering, Hankuk University of Foreign Studies, Yongin 17035, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seok-Lyong","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Industrial and Management Engineering, Hankuk University of Foreign Studies, Yongin 17035, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"103147","DOI":"10.1016\/j.ergon.2021.103147","article-title":"In-field instrumented ergonomic risk assessment: Inertial measurement units versus Kinect V2","volume":"84","author":"Humadi","year":"2021","journal-title":"Int. J. Ind. Ergon."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1555","DOI":"10.1080\/00140139.2021.1903084","article-title":"Development and evaluation of the novel postural loading on the entire body assessment","volume":"64","author":"Kee","year":"2021","journal-title":"Ergonomics"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1090","DOI":"10.1177\/1071181319631174","article-title":"A deep learning-based RULA method for working posture assessment","volume":"63","author":"Li","year":"2019","journal-title":"Proc. Hum. Factors Ergon. Soc. Annu. Meet."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"514","DOI":"10.1016\/j.aei.2018.08.020","article-title":"Automated ergonomic risk monitoring using body-mounted sensors and machine learning","volume":"38","author":"Nath","year":"2018","journal-title":"Adv. Eng. Inform."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"103145","DOI":"10.1016\/j.ergon.2021.103145","article-title":"A generic algorithm for computing optimal ergonomic postures during working in an industrial environment","volume":"84","author":"Verstraten","year":"2021","journal-title":"Int. J. Ind. Ergon."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"103521","DOI":"10.1016\/j.autcon.2020.103521","article-title":"3D fuzzy ergonomic analysis for rapid workplace design and modification in construction","volume":"123","author":"Wang","year":"2020","journal-title":"Autom. Constr."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Donisi, L., Cesarelli, G., Coccia, A., Panigazzi, M., Capodaglio, E., and D\u2019Addio, G. (2021). Work-Related Risk Assessment According to the Revised NIOSH Lifting Equation: A Preliminary Study Using a Wearable Inertial Sensor and Machine Learning. Sensors, 21.","DOI":"10.3390\/s21082593"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Colim, A., Faria, C., Braga, A.C., Sousa, N., Rocha, L., Carneiro, P., Costa, N., and Arezes, P. (2020). Towards an Ergonomic Assessment Framework for Industrial Assembly Workstations\u2014A Case Study. Appl. Sci., 10.","DOI":"10.3390\/app10093048"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Huang, C., Kim, W., Zhang, Y., and Xiong, S. (2020). Development and Validation of a Wearable Inertial Sensors-Based Automated System for Assessing Work-Related Musculoskeletal Disorders in the Workspace. Int. J. Environ. Res. Public Health, 17.","DOI":"10.3390\/ijerph17176050"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"103344","DOI":"10.1016\/j.apergo.2020.103344","article-title":"Intraoperative posture and workload assessment in vascular surgery","volume":"92","author":"Norasi","year":"2020","journal-title":"Appl. Ergon."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.apergo.2019.05.004","article-title":"RGB-D ergonomic assessment system of adopted working postures","volume":"80","author":"Abobakr","year":"2019","journal-title":"Appl. Ergon."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Chatzis, T., Konstantinidis, D., and Dimitropoulos, K. (2022). Automatic Ergonomic Risk Assessment Using a Variational Deep Network Architecture. Sensors, 22.","DOI":"10.3390\/s22166051"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"562","DOI":"10.1016\/j.apergo.2016.10.015","article-title":"Validation of an ergonomic assessment method using Kinect data in real workplace conditions","volume":"65","author":"Plantard","year":"2017","journal-title":"Appl. Ergon."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40648-022-00222-y","article-title":"Rapid prototyping for series of tasks in atypical environment: Robotic system with reliable program-based and flexible learning-based approaches","volume":"9","author":"Ito","year":"2022","journal-title":"ROBOMECH J."},{"key":"ref_15","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_16","doi-asserted-by":"crossref","first-page":"106816","DOI":"10.1016\/j.cie.2020.106816","article-title":"Ergonomic risk assessment based on computer vision and machine learning","volume":"149","author":"Bajo","year":"2020","journal-title":"Comput. Ind. Eng."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TIM.2020.3045841","article-title":"A CNN-LSTM Hybrid Model for Wrist Kinematics Estimation Using Surface Electromyography","volume":"70","author":"Bao","year":"2020","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1068","DOI":"10.1109\/TNSRE.2021.3086401","article-title":"Inter-Subject Domain Adaptation for CNN-Based Wrist Kinematics Estimation Using sEMG","volume":"29","author":"Bao","year":"2021","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_19","unstructured":"Senjaya, W.F., Prathama, F., Setiawan, F., Prabono, A.G., Yahya, B.N., and Lee, S.L. (2020, January 23\u201325). Automated RULA for a sequence of activities based on sensor data. Proceedings of the 2020 Fall Conference of the Korean Society of Industrial Engineering, Seoul, Republic of Korea."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"645153","DOI":"10.3389\/frvir.2021.645153","article-title":"A Review on Virtual Reality Skill Training Applications","volume":"2","author":"Xie","year":"2021","journal-title":"Front. Virtual Real."},{"key":"ref_21","unstructured":"Charles, S.K. (2008). It\u2019s All in the Wrist: A Quantitative Characterization of Human Wrist Control, Massachusetts Institute of Technology."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13673-019-0194-5","article-title":"Multi-sensor fusion based on multiple classifier systems for human activity identification","volume":"9","author":"Nweke","year":"2019","journal-title":"Human-Centric Comput. Inf. Sci."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"103040","DOI":"10.1016\/j.ergon.2020.103040","article-title":"Improved work organization to increase the productivity in manual brick manufacturing unit of West Bengal, India","volume":"81","author":"Das","year":"2021","journal-title":"Int. J. Ind. Ergon."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.procir.2018.03.198","article-title":"Automatic assessment of the ergonomic risk for manual manufacturing and assembly activities through optical motion capture technology","volume":"72","author":"Bortolini","year":"2018","journal-title":"Procedia CIRP"},{"key":"ref_25","first-page":"275","article-title":"Skeleton-free RULA ergonomic assessment using Kinect sensors","volume":"11","author":"Nahavandi","year":"2017","journal-title":"Intell. Decis. Technol."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Tamantini, C., Cordella, F., Lauretti, C., and Zollo, L. (2021). The WGD\u2014A Dataset of Assembly Line Working Gestures for Ergonomic Analysis and Work-Related Injuries Prevention. Sensors, 21.","DOI":"10.3390\/s21227600"},{"key":"ref_27","unstructured":"Slyper, R., and Hodgins, J.K. (2008, January 7\u20139). Action Capture with Accelerometers. Proceedings of the 2008 ACM SIGGRAPH\/Eurographics Symposium on Computer Animation, Dublin, Ireland."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Mousas, C. (2017). Full-Body Locomotion Reconstruction of Virtual Characters Using a Single Inertial Measurement Unit. Sensors, 17.","DOI":"10.3390\/s17112589"},{"key":"ref_29","unstructured":"Lawrence, N.D. (2003, January 8\u201313). Gaussian Process Latent Variable Models for Visualisation of High Dimensional Data. Proceedings of the 16th International Conference on Neural Information Processing Systems, Vancouver, BC, Canada."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1111\/cgf.12469","article-title":"Data-Driven Reconstruction of Human Locomotion Using a Single Smartphone","volume":"33","author":"Eom","year":"2014","journal-title":"Comput. Graph. Forum"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"3234","DOI":"10.1109\/TIE.2011.2148671","article-title":"Towards Miniaturization of a MEMS-Based Wearable Motion Capture System","volume":"58","author":"Brigante","year":"2011","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_32","unstructured":"Doniyorbek, K., and Jung, K. (2020). Development of a Semi-Automatic Rapid Entire Body Assessment System using the Open Pose and a Single Working Image. 2019 Fall Conference of the Korean Society of Industrial Engineering, Springer."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"481","DOI":"10.1016\/j.apergo.2017.02.015","article-title":"Real time RULA assessment using Kinect v2 sensor","volume":"65","author":"Manghisi","year":"2017","journal-title":"Appl. Ergon."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.jbiomech.2018.01.012","article-title":"A computer vision based method for 3D posture estimation of symmetrical lifting","volume":"69","author":"Mehrizi","year":"2018","journal-title":"J. Biomech."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1016\/j.autcon.2018.11.012","article-title":"Automated post-3D visualization ergonomic analysis system for rapid workplace design in modular construction","volume":"98","author":"Li","year":"2018","journal-title":"Autom. Constr."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1080\/10803548.2018.1452666","article-title":"An ergonomics study on wrist posture when using laparoscopic tools in four techniques in minimally invasive surgery","volume":"24","author":"Bartnicka","year":"2018","journal-title":"Int. J. Occup. Saf. Ergon."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"S\u00e1nchez-Margallo, J.A., Gonz\u00e1lez, A.G., Moruno, L.G., G\u00f3mez-Blanco, J.C., Pagador, J.B., and S\u00e1nchez-Margallo, F.M. (2020). Comparative Study of the Use of Different Sizes of an Ergonomic Instrument Handle for Laparoscopic Surgery. Appl. Sci., 10.","DOI":"10.3390\/app10041526"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"564","DOI":"10.1016\/j.apergo.2013.07.016","article-title":"Effects of forearm and palm supports on the upper extremity during computer mouse use","volume":"45","author":"Onyebeke","year":"2014","journal-title":"Appl. Ergon."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1007\/978-3-319-69182-4_9","article-title":"Early Classification of Multivariate Time Series Based on Piecewise Aggregate Approximation","volume":"10594","author":"Ma","year":"2017","journal-title":"Lect. Notes Comput. Sci."},{"key":"ref_40","unstructured":"Middlesworth, M. (2021, July 19). A Step-by-Step Guide Rapid Upper Limb Assessment (RULA). Ergonomics Plus. Available online: www.ergo-plus.com."},{"key":"ref_41","unstructured":"Gellert, W., Hellwich, M., K\u00e4stner, H., and K\u00fcstner, H. (2012). VNR Concise Encyclopedia of Mathematics, Springer Science & Business Media. [2nd ed.]."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Cassisi, C., Montalto, P., Aliotta, M., Cannata, A., and Pulvirenti, A. (2012). Similarity Measures and Dimensionality Reduction Techniques for Time Series Data Mining. Advances in Data Mining Knowledge Discovery and Applications, IntechOpen.","DOI":"10.5772\/49941"},{"key":"ref_43","unstructured":"Ferguson, D. (2020, December 28). Therbligs: The Keys to Simplifying Work. Available online: http:\/\/web.mit.edu\/allanmc\/www\/Therblgs.pdf."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"2489","DOI":"10.1007\/s12652-019-01294-2","article-title":"Using Therbligs to embed intelligence in workpieces for digital assistive assembly","volume":"11","author":"Oyekan","year":"2019","journal-title":"J. Ambient Intell. Humaniz. Comput."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/22\/8898\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:20:24Z","timestamp":1760145624000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/22\/8898"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,17]]},"references-count":44,"journal-issue":{"issue":"22","published-online":{"date-parts":[[2022,11]]}},"alternative-id":["s22228898"],"URL":"https:\/\/doi.org\/10.3390\/s22228898","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,11,17]]}}}