Motion Capture Technologies for Ergonomics: A Systematic Literature Review
Open accessAbstract
Muscular skeletal disorder is a difficult challenge faced by the working population. Motion capture (MoCap) is used for recording the movement of people for clinical, ergonomic and rehabilitation solutions. However, knowledge barriers about these MoCap systems have made them difficult to use for many people. Despite this, no state-of-the-art literature review on MoCap systems for human clinical, rehabilitation and ergonomic analysis has been conducted. A medical diagnosis using AI applies machine learning algorithms and motion capture technologies to analyze patient data, enhancing diagnostic accuracy, enabling early disease detection and facilitating personalized treatment plans. It revolutionizes healthcare by harnessing the power of data-driven insights for improved patient outcomes and efficient clinical decision-making. The current review aimed to investigate: (i) the most used MoCap systems for clinical use, ergonomics and rehabilitation, (ii) their application and (iii) the target population. We used preferred reporting items for systematic reviews and meta-analysis guidelines for the review. Google Scholar, PubMed, Scopus and Web of Science were used to search for relevant published articles. The articles obtained were scrutinized by reading the abstracts and titles to determine their inclusion eligibility. Accordingly, articles with insufficient or irrelevant information were excluded from the screening. The search included studies published between 2013 and 2023 (including additional criteria). A total of 40 articles were eligible for review. The selected articles were further categorized in terms of the types of MoCap used, their application and the domain of the experiments. This review will serve as a guide for researchers and organizational management.
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Cites
Wireless sensor network survey
Yick, J., Mukherjee, B., & Ghosal, D. (2008) · Computer Networks · doi:10.1016/j.comnet.2008.04.002 · Cited by 6,291 · see citing works
IMU-Based Joint Angle Measurement for Gait Analysis
Seel, T., Raisch, J., & Schauer, T. (2014) · Sensors · doi:10.3390/s140406891 · Cited by 871 · see citing works
Colyer, S., Evans, M., Cosker, D. P., & Salo, A. (2018) · Sports Medicine - Open · doi:10.1186/s40798-018-0139-y · Cited by 635 · see citing works
Accuracy of human motion capture systems for sport applications; state‐of‐the‐art review
van der Kruk, E., & Reijne, M. M. (2018) · European Journal of Sport Science · doi:10.1080/17461391.2018.1463397 · Cited by 522 · see citing works
Innovative system for real-time ergonomic feedback in industrial manufacturing
Vignais, N., Miezal, M., Bleser, G., Mura, K., Gorecky, D., & Marin, F. (2012) · Applied Ergonomics · doi:10.1016/j.apergo.2012.11.008 · Cited by 335 · see citing works
Kobsar, D., Charlton, J. M., Tse, C. T. F., Esculier, J.-F., Graffos, A., Krowchuk, N. M., Thatcher, D., & Hunt, M. A. (2020) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-020-00685-3 · Cited by 324 · see citing works
Motion Capture Technology in Industrial Applications: A Systematic Review
Menolotto, M., Komaris, D.-S., Tedesco, S. A., O’Flynn, B., & Walsh, M. J. (2020) · Sensors · doi:10.3390/s20195687 · Cited by 308 · see citing works
Additional Virtual Reality Training Using Xbox Kinect in Stroke Survivors with Hemiplegia
Sin, H., & Lee, G. (2013) · American Journal of Physical Medicine & Rehabilitation · doi:10.1097/phm.0b013e3182a38e40 · Cited by 226 · see citing works
Clark, R. A., Mentiplay, B. F., Hough, E. J., & Pua, Y. (2018) · Gait & Posture · doi:10.1016/j.gaitpost.2018.11.029 · Cited by 209 · see citing works
Validity of the Kinect for Gait Assessment: A Focused Review
Springer, S., & Yogev‐Seligmann, G. (2016) · Sensors · doi:10.3390/s16020194 · Cited by 204 · see citing works
Evaluation of Pose Tracking Accuracy in the First and Second Generations of Microsoft Kinect
Wang, Q., Kurillo, G., Ofli, F., & Bajcsy, R. (2015) · IEEE International Conference on Healthcare Informatics (ICHI) · doi:10.1109/ichi.2015.54 · Cited by 199 · see citing works
Motion Analysis System (MAS) for production and ergonomics assessment in the manufacturing processes
Bortolini, M., Faccio, M., Gamberi, M., & Pilati, F. (2018) · Computers & Industrial Engineering · doi:10.1016/j.cie.2018.10.046 · Cited by 168 · see citing works
Schmitz, A., Ye, M., Shapiro, R., Yang, R., & Noehren, B. W. (2013) · Journal of Biomechanics · doi:10.1016/j.jbiomech.2013.11.031 · Cited by 163 · see citing works
Accuracy of an optical active-marker system to track the relative motion of rigid bodies
Maletsky, L. P., Sun, J., & Morton, N. A. (2006) · Journal of Biomechanics · doi:10.1016/j.jbiomech.2006.01.017 · Cited by 152 · see citing works
Biomechanical evaluation of a new passive back support exoskeleton
Koopman, A. S., Näf, M. B., Baltrusch, S. J., Kingma, I., Rodriguez‐Guerrero, C., Babič, J., de Looze, M. P., & van Dieën, J. H. (2020) · Journal of Biomechanics · doi:10.1016/j.jbiomech.2020.109795 · Cited by 152 · see citing works
Milosevic, B., Leardini, A., & Farella, E. (2020) · BioMedical Engineering OnLine · doi:10.1186/s12938-020-00762-7 · Cited by 103 · see citing works
Gao, L., Zhang, G., Yu, B., Qiao, Z., & Wang, J. (2020) · Measurement · doi:10.1016/j.measurement.2020.108252 · Cited by 91 · see citing works
Real Time Ergonomic Assessment for Assembly Operations Using Kinect
Haggag, H., Hossny, M., Nahavandi, S., & Creighton, D. (2013) · UKSim International Conference on Computer Modelling and Simulation (UKSim) · doi:10.1109/uksim.2013.105 · Cited by 89 · see citing works
The development and evaluation of a fully automated markerless motion capture workflow
Needham, L., Evans, M., Wade, L., Cosker, D. P., McGuigan, P. M., Bilzon, J., & Colyer, S. (2022) · Journal of Biomechanics · doi:10.1016/j.jbiomech.2022.111338 · Cited by 84 · see citing works
Merino, G. S. A. D., da Silva, L., de Mattos, D. L., Guimarães, B. M. D., & Merino, E. A. D. (2018) · International Journal of Industrial Ergonomics · doi:10.1016/j.ergon.2018.10.004 · Cited by 75 · see citing works
A kinematic and kinetic dataset of 18 above-knee amputees walking at various speeds
Hood, S., Ishmael, M. K., Gunnell, A. J., Foreman, K. B., & Lenzi, T. (2020) · Scientific Data · doi:10.1038/s41597-020-0494-7 · Cited by 74 · see citing works
Lebleu, J., Gosseye, T. P., Detrembleur, C., Mahaudens, P., Cartiaux, O., & Penta, M. (2020) · Sensors · doi:10.3390/s20030715 · Cited by 69 · see citing works
Lebel, K., Boissy, P., Nguyen, H., & Duval, C. (2017) · BioMedical Engineering OnLine · doi:10.1186/s12938-017-0347-6 · Cited by 65 · see citing works
A 2D Markerless Gait Analysis Methodology: Validation on Healthy Subjects
Castelli, A., Paolini, G., Cereatti, A., & Croce, U. D. (2015) · Computational and Mathematical Methods in Medicine · doi:10.1155/2015/186780 · Cited by 64 · see citing works
Assessment of Parkinsonian gait in older adults with dementia via human pose tracking in video data
Sabo, A., Mehdizadeh, S., Ng, K.-D., Iaboni, A., & Taati, B. (2020) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-020-00728-9 · Cited by 60 · see citing works
Semi-Automatic Sensor-to-Body Calibration of Inertial Sensors on Lower Limb Using Gait Recording
Nazarahari, M., & Rouhani, H. (2019) · IEEE Sensors Journal · doi:10.1109/jsen.2019.2939981 · Cited by 57 · see citing works
Perrott, M. A., Pizzari, T., Cook, J. L., & McClelland, J. A. (2016) · Gait & Posture · doi:10.1016/j.gaitpost.2016.10.020 · Cited by 52 · see citing works
Comparison of Kinect and Vicon Motion Capture of Upper-Body Joint Angle Tracking
Schlagenhauf, F., Sreeram, S., & Singhose, W. (2018) · International Conference on Control and Automation · doi:10.1109/icca.2018.8444349 · Cited by 48 · see citing works
Trujillo, J. P., Vaitonyté, J., Simanova, I., & Özyürek, A. (2018) · Behavior Research Methods · doi:10.3758/s13428-018-1086-8 · Cited by 47 · see citing works
Computer-automated ergonomic analysis based on motion capture and assembly simulation
Puthenveetil, S. C., Daphalapurkar, C. P., Zhu, W., Leu, M. C., Liu, X. F., Gilpin-Mcminn, J. K., & Snodgrass, S. D. (2015) · Virtual Reality · doi:10.1007/s10055-015-0261-9 · Cited by 44 · see citing works
Monnet, T., Samson, M., Bernard, A., David, L., & Lacouture, P. (2014) · Sports Engineering · doi:10.1007/s12283-014-0152-4 · Cited by 43 · see citing works
Kang, Y., & Chang, Y. (2019) · Journal of Applied Research in Intellectual Disabilities · doi:10.1111/jar.12587 · Cited by 43 · see citing works
A Deep Neural Network-based method for estimation of 3D lifting motions
Mehrizi, R., Peng, X., Xu, X., Zhang, S., & Li, K. (2018) · Journal of Biomechanics · doi:10.1016/j.jbiomech.2018.12.022 · Cited by 41 · see citing works
Upper extremity coordination strategies depending on task demand during a basic daily activity
Ricci, F. P. F. M., Santiago, P. R. P., Zampar, A. C., Pinola, L. N., & Fonseca, M. D. C. R. (2015) · Gait & Posture · doi:10.1016/j.gaitpost.2015.07.061 · Cited by 40 · see citing works
Assessing work-related risk factors for musculoskeletal knee disorders in construction roofing tasks
Breloff, S. P., Dutta, A., Dai, F., Sinsel, E. W., Warren, C. M., Ning, X., & Wu, J. Z. (2019) · Applied Ergonomics · doi:10.1016/j.apergo.2019.102901 · Cited by 38 · see citing works
Ryu, J., Alwasel, A., Haas, C. T., & Abdel-Rahman, E. M. (2020) · Journal of Construction Engineering and Management · doi:10.1061/(asce)co.1943-7862.0001889 · Cited by 38 · see citing works
Wirth, M. A., Fischer, G., Verdú, J., Reissner, L., Balocco, S., & Calcagni, M. (2019) · Sensors · doi:10.3390/s19235297 · Cited by 37 · see citing works
Tamura, H., Tanaka, R., & Kawanishi, H. (2020) · Journal of Biomechanics · doi:10.1016/j.jbiomech.2020.109929 · Cited by 35 · see citing works
Steinebach, T., Grosse, E. H., Glock, C. H., Wakula, J., & Lunin, A. (2020) · Human Factors and Ergonomics in Manufacturing & Service Industries · doi:10.1002/hfm.20840 · Cited by 33 · see citing works
Chakraborty, S., Nandy, A., Yamaguchi, T., Bonnet, V., & Venture, G. (2020) · Journal of Biomechanics · doi:10.1016/j.jbiomech.2020.109718 · Cited by 32 · see citing works
Fleron, M. K., Ubbesen, N. C. H., Battistella, F., Dejtiar, D. L., & Oliveira, A. S. (2018) · Sports Biomechanics · doi:10.1080/14763141.2017.1409259 · Cited by 31 · see citing works
Ferrari, E., Gamberi, M., Pilati, F., & Regattieri, A. (2018) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2018.08.329 · Cited by 29 · see citing works
Body center of mass trajectory and mechanical energy using inertial sensors: a feasible stride?
Pavei, G., Salis, F., Cereatti, A., & Bergamini, E. (2020) · Gait & Posture · doi:10.1016/j.gaitpost.2020.04.012 · Cited by 29 · see citing works
Forces: A Motion Capture-Based Ergonomic Method for the Today’s World
Marín, J., & Marín, J. J. (2021) · Sensors · doi:10.3390/s21155139 · Cited by 27 · see citing works
Postural Control in Workplace Safety: Role of Occupational Footwear and Workload
Chander, H., Garner, J. C., Wade, C., & Knight, A. C. (2017) · Safety · doi:10.3390/safety3030018 · Cited by 26 · see citing works
A comparison of lumbar spine and muscle loading between male and female workers during box transfers
Gagnon, D. J., Plamondon, A., & Larivière, C. (2018) · Journal of Biomechanics · doi:10.1016/j.jbiomech.2018.09.017 · Cited by 25 · see citing works
Muthukrishnan, N., Abbas, J. J., & Krishnamurthi, N. (2020) · Sensors · doi:10.3390/s20226417 · Cited by 25 · see citing works
Brunner, O., Mertens, A., Nitsch, V., & Brandl, C. (2021) · International Journal of Occupational Safety and Ergonomics · doi:10.1080/10803548.2021.1954791 · Cited by 24 · see citing works
A High-Fidelity Wearable System for Measuring Lower-Limb Kinetics and Kinematics
Abdelhady, M., van den Bogert, A. J., & Simon, D. (2019) · IEEE Sensors Journal · doi:10.1109/jsen.2019.2940517 · Cited by 23 · see citing works
Markerless Motion Capture Integrated with Human Modeling for Virtual Ergonomics
Colombo, G., Regazzoni, D., & Rizzi, C. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-39182-8_37 · Cited by 22 · see citing works
Lavender, S. A., Sommerich, C. M., Bigelow, S., Weston, E. B., Seagren, K. E., Pay, N. A., Sillars, D., Ramachandran, V., Sun, C., Xu, Y., et al. (2019) · Applied Ergonomics · doi:10.1016/j.apergo.2019.102910 · Cited by 22 · see citing works
Takayasu, K., Yoshida, K., Mishima, T., Watanabe, M., Matsuda, T., & Kinoshita, H. (2018) · The American Journal of Surgery · doi:10.1016/j.amjsurg.2018.06.026 · Cited by 20 · see citing works
Michaud, F., Lugrís, U., & Cuadrado, J. (2022) · Sensors · doi:10.3390/s22134796 · Cited by 20 · see citing works
Inertial Motion Capture-Based Estimation of L5/S1 Moments during Manual Materials Handling
Muller, A., Mecheri, H., Corbeil, P., Plamondon, A., & Robert‐Lachaine, X. (2022) · Sensors · doi:10.3390/s22176454 · Cited by 19 · see citing works
Assessment of a markerless motion analysis system for manual wheelchair application
Rammer, J. R., Slavens, B. A., Krzak, J. J., Winters, J. M., Riedel, S. A., & Harris, G. F. (2018) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-018-0444-1 · Cited by 18 · see citing works
Motion capture-based animated characters for the study of speech–gesture integration
Nirme, J., Haake, M., Gulz, A., & Gullberg, M. (2019) · Behavior Research Methods · doi:10.3758/s13428-019-01319-w · Cited by 18 · see citing works
Markerless Gait Analysis Vision System for Real-time Gait Monitoring
André, J., Lopes, J. M., Palermo, M., Gonçalves, D., Matias, A., Pereira, F., Afonso, J. A., Seabra, E. A. R., Cerqueira, J., & Santos, C. P. (2020) · IEEE International Conference on Autonomous Robot Systems and Competitions · doi:10.1109/icarsc49921.2020.9096121 · Cited by 17 · see citing works
Waldman, H. S., Smith, J. W., Lamberth, J., Fountain, B. J., & McAllister, M. J. (2019) · The Journal of Strength and Conditioning Research · doi:10.1519/jsc.0000000000003354 · Cited by 16 · see citing works
Inertial Sensor-Based Instrumented Cane for Real-Time Walking Cane Kinematics Estimation
Fernandez, I. G., Ahmad, S. A., & Wada, C. (2020) · Sensors · doi:10.3390/s20174675 · Cited by 15 · see citing works
Peak sagittal plane spine kinematics in female gymnasts with and without a history of low back pain
Pimentel, R. E., Potter, M. N., Carollo, J. J., Howell, D. R., & Sweeney, E. A. (2020) · Clinical Biomechanics · doi:10.1016/j.clinbiomech.2020.105019 · Cited by 14 · see citing works
Michaud, F., Pazos, R., Lugrís, U., & Cuadrado, J. (2023) · Sensors · doi:10.3390/s23115116 · Cited by 12 · see citing works
Bruxism as a new risk factor of musculo-skeletal disorders?
Mainjot, A. K. J., Oudkerk, J., Bekaert, S., Dardenne, N., Streel, S., Koenig, V., Grenade, C., Davarpanah, A., Donneau, A., Forthomme, B., et al. (2023) · Journal of Dentistry · doi:10.1016/j.jdent.2023.104555 · Cited by 12 · see citing works
Perruccio, A. V., Yip, C., Power, J. D., Cañizares, M., & Badley, E. M. (2018) · Arthritis Care & Research · doi:10.1002/acr.23583 · Cited by 10 · see citing works
Monitoring patient movement with boron neutron capture therapy and motion capture technology
Kumada, H., Takada, K., Terunuma, T., Aihara, T., Matsumura, A., Sakurai, H., & Sakae, T. (2020) · Applied Radiation and Isotopes · doi:10.1016/j.apradiso.2020.109208 · Cited by 10 · see citing works
A Methodology to Create 3D Body Models in Motion
Parrilla, E., Nicolau, A. V. R., Solves, J.-A., Ballester, A., Nácher, B., Alemany, S., & Garrido, D. (2020) · Advances in intelligent systems and computing · doi:10.1007/978-3-030-51064-0_39 · Cited by 10 · see citing works
Quaternion statistics applied to the classification of motion capture data
Świtoński, A., Josiński, H., Michalczuk, A., & Wojciechowski, K. W. (2020) · Expert Systems with Applications · doi:10.1016/j.eswa.2020.113813 · Cited by 10 · see citing works
Janssen, M. M. H. P., Peeters, L. H. C., & de Groot, I. J. M. (2020) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-020-00757-4 · Cited by 9 · see citing works
Marker-based motion capture for measuring joint kinematics in leg swing simulator
Yunardi, R. T., & Winarno, W. (2017) · International Conference on Instrumentation, Control, and Automation (ICA) · doi:10.1109/ica.2017.8068405 · Cited by 7 · see citing works
Biomechanical and physiological load carrying efficiency of two firefighter harness variations
Kakar, R. S., Tome, J. M., King, D. L., & Jin, Z. M. (2018) · Cogent Engineering · doi:10.1080/23311916.2018.1502231 · Cited by 6 · see citing works
Shoulder muscle activity in off-axis pushing and pulling tasks
McDonald, A. C., Tsang, C., Meszaros, K. A., & Dickerson, C. R. (2019) · International Journal of Industrial Ergonomics · doi:10.1016/j.ergon.2019.102892 · Cited by 6 · see citing works
Ferrández-Laliena, L., Vicente-Pina, L., Sánchez-Rodríguez, R., Orantes-González, E., Heredia‐Jimenez, J., Lucha-López, M. O., Hidalgo-García, C., & Tricás-Moreno, J. M. (2023) · Diagnostics · doi:10.3390/diagnostics13050928 · Cited by 5 · see citing works
Seol, J., Yoon, K., & Kim, K. G. (2022) · Diagnostics · doi:10.3390/diagnostics12123179 · Cited by 2 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [31]Gandolfi E. Virtual Reality and Augmented Reality in Europe Springer International Publishing Berlin/Heidelberg, Germany 2018 Volume 2 978-3-030-01789-7
Cited by
Sorted by citations
Younis, H. A., Eisa, T. A. E., Nasser, M., Sahib, T. M., Noor, A. A., Alyasiri, O. M., Salisu, S., Hayder, I. M., & Younis, H. A. (2024) · Diagnostics · doi:10.3390/diagnostics14010109 · Cited by 242 · see citing works
Self-citationA Novel IMU-Based System for Work-Related Musculoskeletal Disorders Risk Assessment
Baklouti, S., Chaker, A., Rezgui, T., Sahbani, A., Bennour, S., & Laribi, M. A. (2024) · Sensors · doi:10.3390/s24113419 · Cited by 36 · see citing works
Szabo, D. A., Neagu, N. E., Teodorescu, S., Apostu, M., Predescu, C., Pârvu, C., & Veres, C. (2023) · Sensors · doi:10.3390/s23218950 · Cited by 35 · see citing works
Validation of markerless vision-based motion capture for ergonomics risk assessment
Bonakdar, A., Riahi, N., Shakourisalim, M., Miller, L., Tavakoli, M., Rouhani, H., & Golabchi, A. (2025) · International Journal of Industrial Ergonomics · doi:10.1016/j.ergon.2025.103734 · Cited by 19 · see citing works
Rahman, M. H., Hasan, M. R., Chowdhury, N. I., Syed, M. A. B., & Farah, M. U. (2024) · Digital engineering. · doi:10.1016/j.dte.2024.100002 · Cited by 18 · see citing works
Digital and Virtual Technologies for Work-Related Biomechanical Risk Assessment: A Scoping Review
Filho, P. C. A., Colim, A., Jesus, C., Lopes, S. I., & Carneiro, ́. (2024) · Safety · doi:10.3390/safety10030079 · Cited by 22 · see citing works
González-Alonso, J., Martín-Tapia, P., González‐Ortega, D., Antón‐Rodríguez, M., Pernas, F. J. D., & Martínez‐Zarzuela, M. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.127212 · Cited by 15 · see citing works
Mind, Machine, and Meaning: Cognitive Ergonomics and Adaptive Interfaces in the Age of Industry 5.0
Ioniță, A.-R., Anghel, D.-C., & Boudouh, T. (2025) · Applied Sciences · doi:10.3390/app15147703 · Cited by 13 · see citing works
Language-Assisted Skeleton Action Understanding for Skeleton-Based Temporal Action Segmentation
Ji, H., Chen, B., Xu, X., Ren, W., Wang, Z., & Liu, H. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72949-2_23 · Cited by 12 · see citing works
Angelova, R. A. (2025) · Textiles · doi:10.3390/textiles5040049 · Cited by 10 · see citing works
Cruciata, L., Contino, S., Ciccarelli, M., Pirrone, R., Mostarda, L., Papetti, A., & Piangerelli, M. (2025) · Sensors · doi:10.3390/s25154750 · Cited by 10 · see citing works
González‐Alonso, J., Simón-Martínez, C., Antón‐Rodríguez, M., González‐Ortega, D., Pernas, F. J. D., & Martínez‐Zarzuela, M. (2024) · Safety Science · doi:10.1016/j.ssci.2024.106431 · Cited by 10 · see citing works
Kakegawa, K., & Matsuda, T. (2024) · Sensors · doi:10.3390/s25010016 · Cited by 5 · see citing works
Safari, M., Naserbakht, A., Kouhi, A. B., & Varmazyar, S. (2025) · Work · doi:10.1177/10519815251349793 · Cited by 5 · see citing works
Matsuda, T., Watanabe, J., Sotokawa, T., Shishime, T., & Katoh, H. (2025) · Journal of Functional Morphology and Kinesiology · doi:10.3390/jfmk10030356 · Cited by 4 · see citing works
TSURUMACHI, N., Masui, K., Kazuki, D. O. I., MATSUYAMA, S., Tsunoda, N., Kiyono, T., & Asai, T. (2025) · Minerva Anestesiologica · doi:10.23736/s0375-9393.25.18641-0 · Cited by 4 · see citing works
Easy Rocap: A Low-Cost and Easy-to-Use Motion Capture System for Drones
Wang, H., Chen, C., He, Y., Sun, S., Li, L., Xu, Y., & Yang, B. (2024) · Drones · doi:10.3390/drones8040137 · Cited by 4 · see citing works
Non-contact tracking of shoulder bones using ultrasound and stereophotogrammetry
Sewify, A., Lavaill, M., O’Rourke, D., Antico, M., Pivonka, P., Fontanarosa, D., & Martelli, S. (2025) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2025.1514568 · Cited by 3 · see citing works
Bertoli, A., Nini, M., Cibrario, V., Vargas, M., Perona, P., Rossi, L., Benedetti, L., Nicolinti, A., & Fantuzzi, C. (2025) · Machines · doi:10.3390/machines13040303 · Cited by 3 · see citing works
Influence of motion capture camera’s self-heating on optoelectronic plethysmography accuracy
Gaillard, L., Stubbe, L., Riquet, D., & Houel, N. (2025) · Measurement · doi:10.1016/j.measurement.2025.117523 · Cited by 3 · see citing works
Harnau, E., Breiter, S., & Arlinghaus, J. C. (2024) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2024.09.150 · Cited by 3 · see citing works
Pan, J., Zhou, Z., Gao, Z., Chen, D., Li, F., Baker, J. S., & Gu, Y. (2025) · Proceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine · doi:10.1177/09544119251361341 · Cited by 2 · see citing works
Samani, A. S., Razeghi, M., Abdoli-Eramaki, M., & Choobineh, A. (2026) · BMC Research Notes · doi:10.1186/s13104-026-07886-4 · Cited by 2 · see citing works
Tripathi, C., Arora, M., & Chakrabarti, A. (2024) · Proceedings of the Design Society · doi:10.1017/pds.2024.248 · Cited by 2 · see citing works
Interaction of Intelligent Vehicle-Machine System Based on Gesture Recognition
Xu, W., & Yang, Z. (2024) · International Conference on Electronics and Sustainable Communication Systems (ICESC) · doi:10.1109/icesc60852.2024.10689835 · Cited by 1 · see citing works
Valcheva, D., Kalushkov, T., & Shipkovenski, G. (2025) · BRAIN BROAD RESEARCH IN ARTIFICIAL INTELLIGENCE AND NEUROSCIENCE · doi:10.70594/brain/16.s1/10 · Cited by 1 · see citing works
Gennarelli, I., Varrecchia, T., Chini, G., Martinel, N., Micheloni, C., & Ranavolo, A. (2025) · Sensors · doi:10.3390/s25247427 · Cited by 1 · see citing works
Real-Time Ergonomic Assessment with Fuzzy Logic and RGB-D Sensors
Martinez, C. F., Galvan, F. S., Santos, H. B., Vázquez-Estrada, O., Martinez-De-La-Cruz, D. I., & Ponce-Del-Ángel, F. G. (2026) · Engineering Technology & Applied Science Research · doi:10.48084/etasr.14044 · Cited by 1 · see citing works
Osman, H., de Kanter, D., Boelens, J., Kok, M., & Seth, A. (2026) · Sensors · doi:10.3390/s26123697 · Cited by 1 · see citing works
Younis, H. A., Hayder, I. M., Salisu, S., Muthmainnah, M., Shahid, M., & Younis, H. A. (2024) · International Journal of Education Research and Development · doi:10.52760/ijerd.v4i1.54 · Cited by 1 · see citing works
Self-citationVorapojpisut, S., Sansuk, S., Yindee, P., Panich, D., Puengtanom, V., & Saadprai, S. (2025) · Wearable Technologies · doi:10.1017/wtc.2025.10005 · Cited by 3 · see citing works
Fast calibration method for industrial robot kinematics based on motion capture system
Wang, X., Jia, W., & Cao, J. (2025) · Review of Scientific Instruments · doi:10.1063/5.0278164 · Cited by 1 · see citing works
Moving Experiences - Towards a Conceptual Framework for Performative Artefacts in Museums
Töpfer, F., Christ, E., Yu, Z., Engeln, L., Franke, I. S., & McGinity, M. (2024) · International Conference on Culture and Computer Science (KUI) · doi:10.1145/3719236.3719249 · Cited by 1 · see citing works
Motion Capturing in Learning Factories-Technologies and Application Scenarios
Bittencourt, V., Kolla, S. S. V. K., & Thiede, S. (2025) · Lecture notes in networks and systems · doi:10.1007/978-3-031-98883-7_22 · Cited by 1 · see citing works
Rybnikár, F., Šimon, M., Vránek, P., & Krňoul, M. (2023) · International Conference on Developments in eSystems Engineering (DeSE) · doi:10.1109/dese60595.2023.10469047
Vector Space Modeling of Classical Chinese Dance Movements Based on Motion Capture Technology
Liu, M. (2024) · Applied Mathematics and Nonlinear Sciences · doi:10.2478/amns-2024-3518
Albath, A., & Mischker, T. (2025) · Springer eBooks · doi:10.1007/978-3-662-69363-6_6
Wang, J. (2025) · Applied Mathematics and Nonlinear Sciences · doi:10.2478/amns-2025-0737
Towards a Continuous Ergonomic Evaluation of Manual Workstations in the Digital Factory
Sprenger, J., Braun, N., Reichardt, S., & Kellner, B. (2025) · IEEE International Conference on Industrial Cyber-Physical Systems (ICPS) · doi:10.1109/icps65515.2025.11087913
Zang, J., Pan, X., Cui, Y., Li, X., Wei, F., Chen, Z., & Wang, Z. (2025) · PubMed Central · doi:10.7507/1002-1892.202505056
Tripathi, C., Arora, M., & Chakrabarti, A. (2025) · International Journal of Occupational Safety and Ergonomics · doi:10.1080/10803548.2025.2543162
Lower Limb Motion Estimation Based on a Small Number of Inertial Measurement Units
Zhou, K., He, C., Jin, Y., Zhang, B., Liu, T., & Wang, B. (2025) · IEEE Sensors Journal · doi:10.1109/jsen.2025.3639078
Motion-Controlled Wearables for Physiological Monitoring and Predictive Diagnostics
Deepa, R., Swadhi, R., Udayavani, V., Lakshmi, R., & Rafiq, S. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-8241-8.ch001
Ergonomie in der Wirbelsäulenchirurgie
Scherer, J. N., & Osterhoff, G. (2026) · Die Wirbelsäule · doi:10.1055/a-2588-7408
Pradisi, V., Marini, M. R., Zubiena, F. C. G. D., Palermo, E., Baiocchi, E., Malatesta, S. G., & Cinque, L. (2026) · Scientific Reports · doi:10.1038/s41598-026-46138-0
Bao, Q., Niu, J., Zheng, P., Guo, H., & Zhang, A. (2026) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2026.05.018
From body hulls to musculoskeletal models: Personalized inertial parameter estimation
Gambietz, M., Azam, P. Q., Amon, P., Wechsler, I., Hille, E. M., Menzel, T., Ott, T., Botsch, M., Braun, M., Miehling, J., et al. (2026) · PLoS ONE · doi:10.1371/journal.pone.0349886
A Wireless Analog Interface with Near Frame-Accurate Synchronization for Optical Motion Capture
PIERCE, T., Noble, E., Davis, D. L., Wilkins, J., & Loh, K. J. (2026) · Electronics · doi:10.3390/electronics15132787
Achieving Accurate Head Kinematic Measurement Through a Low-Cost and Flexible System
Chen, L., Guo, H., Tang, R. Y., Chen, J., & Luximon, Y. (2026) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2026.3711304
Inertial human motion capture: From biomechanics to recent sensor fusion methods and back
Kok, M., Weygers, I., Osman, H., Weber, D. O. M., Li, R. K., Seel, T., & Seth, A. (2026) · Journal of Biomechanics · doi:10.1016/j.jbiomech.2026.113542
Bertoli, A., Vargas, M., Tumiotto, D., Araujo, J. M. D. S., Costi, S., Orlandini, S., Cibrario, V., Benedetti, L., & Fantuzzi, C. (2026) · Exploration of Musculoskeletal Diseases · doi:10.37349/emd.2026.1007130
Task-Based Configuration Model for Occupational Safety and Health in Heritage Work Environments
Badea, D. O., Cioca, L., Coman, C., & Posa, M.-V. (2026) · Safety · doi:10.3390/safety12040102
Evaluation of Characteristics of the Body Motion Using 4D Scanning and OpenSim Software
Mizan, R. A., Sadretdinova, N., & Kyosev, Y. K. (2026) · Springer Proceedings in Materials · doi:10.1007/978-3-032-26592-0_9
IMU- and Vision-Based Measurement Techniques for Joint Kinematics: A Narrative Review
Ceriola, L., Molinaro, L., Taborri, J., Patanè, F., & Mileti, I. (2026) · Sensors · doi:10.3390/s26165063
Zhang, M., Nieuwenhuys, A., Boocock, M., & Zhang, Y. (2026) · Applied Ergonomics · doi:10.1016/j.apergo.2026.104866
Bao, W., & He, X. (2026) · International Conference on Modern Sustainable Systems (CMSS) · doi:10.1109/cmss69636.2026.11689037
Hilton, C., Potts, D., Hawkins, K., Halpin, K., Halpin, N., Edwards, A., Seymour, A., Gillies, M. F. P., Fox, I., Stark, A., et al. (2026) · International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS) · doi:10.1145/3797867.3828976
A Systematic Review of the Use of Motion Capture in the Digital Humanities
McArthur, V. (2026) · ACM Computing Surveys · doi:10.1145/3850235
- Authors
- Salisu, S., Ruhaiyem, N. I. R., Eisa, T. A. E., Nasser, M., Saeed, F., & Younis, H. A.
- Affiliations
- Universiti Sains Malaysia (MY)
- King Khalid University (SA)
- Universiti Teknologi Petronas (MY)
- Birmingham City University (GB)
- University of Basrah (IQ)
- Corresponding author
- Salisu, Sani
- Ruhaiyem, Nur Intan Raihana
- ORCID
- Venue
- Diagnostics
- Publisher
- MDPI AG
- Published
- 2023-08-04
- Volume
- 13
- Issue
- 15
- Pages
- 2593
- ISSN
- 2075-4418 (ISSN-L)
- PMC
- PMC10416907
- OpenAlex
- W4385576727
- Cited by
- 58
- References
- 72
- Citations by year
- 2026: 18 · 2025: 24 · 2024: 14 · 2023: 2
- FWCI
- 2.83
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Diagnostics (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- BCU Open Access Repository (Birmingham City University) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- King Khalid University (RGP2/52/44)
- Topics
- Social Sciences › Psychology › Social Psychology › Ergonomics and Musculoskeletal Disorders
- Physical Sciences › Engineering › Control and Systems Engineering › Human Motion and Animation
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Human Pose and Action Recognition
- Keywords
- motion capture system, human factors, musculoskeletal disorders, rehabilitation, clinical application, wearable sensors, machine learning in healthcare, patient data analysis, personalized treatment
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