Human Digital Twin for Fitness Management
Open accessAbstract
Our research work describes a team of human Digital Twins (DTs), each tracking fitness-related measurements describing an athlete's behavior in consecutive days (e.g. food income, activity, sleep). After collecting enough measurements, the DT firstly predicts the physical twin performance during training and, in case of non-optimal result, it suggests modifications in the athlete's behavior. The athlete's team is integrated into SmartFit, a software framework for supporting trainers and coaches in monitoring and manage athletes' fitness activity and results. Through IoT sensors embedded in wearable devices and applications for manual logging (e.g. mood, food income), SmartFit continuously captures measurements, initially treated as the dynamic data describing the current physical twins' status. Dynamic data allows adapting each DT's status and triggering the DT's predictions and suggestions. The analyzed measurements are stored as the historical data, further processed by the DT to update (increase) its knowledge and ability to provide reliable predictions. Results show that, thanks to the team of DTs, SmartFit computes trustable predictions of the physical twins' conditions and produces understandable suggestions which can be used by trainers to trigger optimization actions in the athletes' behavior. Though applied in the sport context, SmartFit can be easily adapted to other monitoring tasks.
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A challenge for athlete human digital twins is that the amount of data and the processing time needed to build individual models constantly increase.
“A challenge from this type of DT is that the amount of data and the processing time needed to build individual models constantly increase.”
From Digital Twin Technology Challenges and Applications: A Comprehensive Review (2022) · cites this paper as [52]
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Digital Twin Technology Challenges and Applications: A Comprehensive Review
Botín-Sanabria, D. M., Mihaita, A.-S., Peimbert-García, R. E., Ramírez-Moreno, M. A., Ramírez-Mendoza, R. A., & Lozoya-Santos, J. D. J. (2022) · Remote Sensing · doi:10.3390/rs14061335 · Cited by 878 · see citing works
Rathore, M. M., Shah, S. A., Shukla, D., Bentafat, E., & Bakiras, S. (2021) · IEEE Access · doi:10.1109/access.2021.3060863 · Cited by 616 · see citing works
Pham, Q.-V., Nguyen, D. C., Huynh-The, T., Hwang, W.-J., & Pathirana, P. N. (2020) · IEEE Access · doi:10.1109/access.2020.3009328 · Cited by 413 · see citing works
Stepin, I., Alonso, J. M., Catala, A., & Pereira-Farina, M. (2021) · IEEE Access · doi:10.1109/access.2021.3051315 · Cited by 376 · see citing works
A probabilistic graphical model foundation for enabling predictive digital twins at scale
Kapteyn, M. G., Pretorius, J. V. R., & Willcox, K. E. (2021) · Nature Computational Science · doi:10.1038/s43588-021-00069-0 · Cited by 363 · see citing works
Chen, J., Yi, C., Okegbile, S. D., Cai, J., & Shen, X. (2023) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2023.3308717 · Cited by 268 · see citing works
Digital twin: Data exploration, architecture, implementation and future
Dihan, M. S., Akash, A. I., Tasneem, Z., Das, P., Das, S. K., Islam, M. R., Islam, M. M., Badal, F. R., Ali, M. F., Ahamed, M. H., et al. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e26503 · Cited by 250 · see citing works
Artificial intelligence in digital twins—A systematic literature review
Kreuzer, T., Papapetrou, P., & Zdravković, J. (2024) · Data & Knowledge Engineering · doi:10.1016/j.datak.2024.102304 · Cited by 240 · see citing works
Human Digital Twin for Personalized Healthcare: Vision, Architecture and Future Directions
Okegbile, S. D., Cai, J., Niyato, D. T., & Yi, C. (2022) · IEEE Network · doi:10.1109/mnet.118.2200071 · Cited by 205 · see citing works
Exploring the revolution in healthcare systems through the applications of digital twin technology
Haleem, A., Javaid, M., Singh, R. P., & Suman, R. (2023) · Biomedical Technology · doi:10.1016/j.bmt.2023.02.001 · Cited by 210 · see citing works
Impactful Digital Twin in the Healthcare Revolution
Hassani, H., Huang, X., & MacFeely, S. (2022) · Big Data and Cognitive Computing · doi:10.3390/bdcc6030083 · Cited by 200 · see citing works
Lattanzi, L., Raffaeli, R., Peruzzini, M., & Pellicciari, M. (2021) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2021.1911003 · Cited by 205 · see citing works
The Future of the Human–Machine Interface (HMI) in Society 5.0
Mourtzis, D., Angelopoulos, J., & Panopoulos, N. (2023) · Future Internet · doi:10.3390/fi15050162 · Cited by 179 · see citing works
Digital Twin Empowered Wireless Healthcare Monitoring for Smart Home
Chen, J., Wang, W. W., Fang, B., Liu, Y., Yu, K., Leung, V. C. M., & Hu, X. (2023) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2023.3310097 · Cited by 184 · see citing works
Hu, Z., Lou, S., Xing, Y., Wang, X., Cao, D., & Lv, C. (2022) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2022.3195635 · Cited by 178 · see citing works
Digital Twins Driven Supply Chain Visibility within Logistics: A New Paradigm for Future Logistics
Moshood, T. D., Nawanir, G., Sorooshian, S., & Okfalisa, O. (2021) · Applied System Innovation · doi:10.3390/asi4020029 · Cited by 195 · see citing works
Roads Infrastructure Digital Twin: A Step Toward Smarter Cities Realization
Marai, O. E., Taleb, T., & Song, J. (2020) · IEEE Network · doi:10.1109/mnet.011.2000398 · Cited by 167 · see citing works
Asad, U., Khan, M., Khalid, A., & Lughmani, W. A. (2023) · Sensors · doi:10.3390/s23083938 · Cited by 172 · see citing works
Digital Twins for Healthcare 4.0—Recent Advances, Architecture, and Open Challenges
Alazab, M., Khan, L. U., Koppu, S., Ramu, S. P., Iyapparaja, M., Boobalan, P., Baker, T., Maddikunta, P. K. R., Gadekallu, T. R., & Aljuhani, A. (2022) · IEEE Consumer Electronics Magazine · doi:10.1109/mce.2022.3208986 · Cited by 148 · see citing works
A unified view of a human digital twin
Miller, M. E., & Spatz, E. (2022) · Human-Intelligent Systems Integration · doi:10.1007/s42454-022-00041-x · Cited by 151 · see citing works
Generative-AI-Driven Human Digital Twin in IoT Healthcare: A Comprehensive Survey
Chen, J., Shi, Y., Yi, C., Du, H., Kang, J., & Niyato, D. T. (2024) · IEEE Internet of Things Journal · doi:10.1109/jiot.2024.3421918 · Cited by 155 · see citing works
Application of Digital Twins in multiple fields
Guo, J., & Lv, Z. (2022) · Multimedia Tools and Applications · doi:10.1007/s11042-022-12536-5 · Cited by 138 · see citing works
Okegbile, S. D., Cai, J., Zheng, H., Chen, J., & Yi, C. (2023) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2023.3310106 · Cited by 133 · see citing works
Intelligent Wearable Systems: Opportunities and Challenges in Health and Sports
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Xames, M. D., & Topcu, T. G. (2024) · IEEE Access · doi:10.1109/access.2023.3349379 · Cited by 131 · see citing works
Mykoniatis, K., & Harris, G. A. (2021) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-020-01724-5 · Cited by 117 · see citing works
Lin, Y., Chen, L., Ali, A., Nugent, C., Cleland, I., Li, R., Ding, J., & Ning, H. (2024) · Journal of Cloud Computing Advances Systems and Applications · doi:10.1186/s13677-024-00691-z · Cited by 112 · see citing works
From Digital Human Modeling to Human Digital Twin: Framework and Perspectives in Human Factors
He, Q., Li, L., Dai, L., Peng, T., Zhang, X., Cai, Y., Zhang, X., & Tang, R. (2024) · Chinese Journal of Mechanical Engineering · doi:10.1186/s10033-024-00998-7 · Cited by 112 · see citing works
Survey on digital twins for Internet of Vehicles: Fundamentals, challenges, and opportunities
Guo, J., Bilal, M., Qiu, Y., Qian, C., Xu, X., & Raymond Choo, K.-K. (2024) · Digital Communications and Networks · doi:10.1016/j.dcan.2022.05.023 · Cited by 99 · see citing works
Digital twin and its applications: A survey
Zhang, R., Wang, F., Cai, J., Wang, Y., Guo, H., & Zheng, J. (2022) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-022-10445-3 · Cited by 104 · see citing works
A Comprehensive Survey of Digital Twins in Healthcare in the Era of Metaverse
Turab, M., & Jamil, S. (2023) · BioMedInformatics · doi:10.3390/biomedinformatics3030039 · Cited by 100 · see citing works
Newrzella, S. R., Franklin, D. W., & Haider, S. (2021) · IEEE Access · doi:10.1109/access.2021.3115055 · Cited by 94 · see citing works
Drummond, D., & Gonsard, A. (2024) · Journal of Medical Internet Research · doi:10.2196/58504 · Cited by 95 · see citing works
Architecture of a Human-Digital Twin as Common Interface for Operator 4.0 Applications
Löcklin, A., Jung, T., Jazdi, N., Ruppert, T., & Weyrich, M. (2021) · Procedia CIRP · doi:10.1016/j.procir.2021.11.077 · Cited by 80 · see citing works
Casiraghi, E., Malchiodi, D., Trucco, G., Frasca, M., Cappelletti, L., Fontana, T., Esposito, A., Avola, E., Jachetti, A., Reese, J. T., et al. (2020) · IEEE Access · doi:10.1109/access.2020.3034032 · Cited by 76 · see citing works
Self-citationWearables and Internet of Things (IoT) Technologies for Fitness Assessment: A Systematic Review
Passos, J., Lopes, S. I., Clemente, F. M., Moreira, P. M., Rico-González, M., Bezerra, P., & Rodrigues, L. P. (2021) · Sensors · doi:10.3390/s21165418 · Cited by 79 · see citing works
Papyshev, G., & Yarime, M. (2021) · Data & Policy · doi:10.1017/dap.2021.17 · Cited by 81 · see citing works
Metaverse and Personal Healthcare
Song, Y.-T., & Qin, J. (2022) · Procedia Computer Science · doi:10.1016/j.procs.2022.10.136 · Cited by 77 · see citing works
A Human-Centric Metaverse Enabled by Brain-Computer Interface: A Survey
Zhu, H. Y., Hieu, N. Q., Hoang, D. T., Nguyen, D. N., & Lin, C. (2024) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2024.3387124 · Cited by 75 · see citing works
Human Digital Twins: A systematic literature review and concept disambiguation for industry 5.0
Gaffinet, B., Ali, J. A. H., Naudet, Y., & Panetto, H. (2025) · Computers in Industry · doi:10.1016/j.compind.2024.104230 · Cited by 79 · see citing works
Digital Twins for Healthcare Using Wearables
Johnson, Z., & Saikia, M. J. (2024) · Bioengineering · doi:10.3390/bioengineering11060606 · Cited by 74 · see citing works
Sustainable Blockchain-Based Digital Twin Management Architecture for IoT Devices
Wang, C., Cai, Z., & Li, Y. (2022) · IEEE Internet of Things Journal · doi:10.1109/jiot.2022.3153653 · Cited by 74 · see citing works
Roadmap to semi-automatic generation of digital twins for brownfield process plants
Sierla, S., Azangoo, M., Rainio, K., Papakonstantinou, N., Fay, A., Honkamaa, P., & Vyatkin, V. V. (2021) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2021.100282 · Cited by 63 · see citing works
Chaparro-Cárdenas, S. L., Ramirez-Bautista, J. A., Terven, J. R., Esparza, D. M. C., Romero-González, J.-A., Ramírez-Pedraza, A., & Chávez‐Urbiola, E. A. (2025) · Healthcare · doi:10.3390/healthcare13141763 · Cited by 70 · see citing works
Digital twins and artificial intelligence
Furini, M., Gaggi, O., Mirri, S., Montangero, M., Pelle, E., Poggi, F., & Prandi, C. (2022) · Communications of the ACM · doi:10.1145/3478281 · Cited by 59 · see citing works
Autonomous Driving Test Method Based on Digital Twin: A Survey
Niaz, A., Shoukat, M. U., Jia, Y., Khan, S., Niaz, F., & Raza, M. U. (2021) · International Conference on Computing, Electronic and Electrical Engineering (ICE Cube) · doi:10.1109/icecube53880.2021.9628341 · Cited by 54 · see citing works
Enabling Digital Twins to Support the UN SDGs
Hassani, H., Huang, X., & MacFeely, S. (2022) · Big Data and Cognitive Computing · doi:10.3390/bdcc6040115 · Cited by 55 · see citing works
A Digital Twin Driven Human-Centric Ecosystem for Industry 5.0
Villani, V., Picone, M., Mamei, M., & Sabattini, L. (2024) · IEEE Transactions on Automation Science and Engineering · doi:10.1109/tase.2024.3410703 · Cited by 55 · see citing works
Twinbase: Open-Source Server Software for the Digital Twin Web
Autiosalo, J., Siegel, J. E., & Tammi, K. (2021) · IEEE Access · doi:10.1109/access.2021.3119487 · Cited by 50 · see citing works
Ruiu, P., Nitti, M., Pilloni, V., Cadoni, M. I., Grosso, E., & Fadda, M. (2024) · Multimodal Technologies and Interaction · doi:10.3390/mti8060048 · Cited by 57 · see citing works
Designing Human Digital Twins for Behaviour-Changing Therapy and Rehabilitation: A Systematic Review
Lauer-Schmaltz, M. W., Cash, P. J., Hansen, J. P., & Maier, A. M. (2022) · Proceedings of the Design Society · doi:10.1017/pds.2022.132 · Cited by 50 · see citing works
Digital twins in healthcare IoT: A systematic review
Kabir, M. R., Shishir, F. S., Shomaji, S., & Ray, S. (2025) · High Confid. Comput. · doi:10.1016/j.hcc.2025.100340 · Cited by 61 · see citing works
Newrzella, S. R., Franklin, D. W., & Haider, S. (2022) · IEEE Access · doi:10.1109/access.2022.3202941 · Cited by 48 · see citing works
Roopa, M. S., & Venugopal, K. R. (2025) · IEEE Access · doi:10.1109/access.2025.3547991 · Cited by 56 · see citing works
An architecture to facilitate the integration of human workers in Industry 4.0 environments
Sparrow, D., Kruger, K., & Basson, A. (2021) · International Journal of Production Research · doi:10.1080/00207543.2021.1937747 · Cited by 24 · see citing works
Andres, A., Roland, M., Wickert, K., Diebels, S., Stöckl, J., Herrmann, S., Reinauer, F., Leibinger, R., Pavlov, A., Schuppener, L., et al. (2025) · Scientific Reports · doi:10.1038/s41598-025-04792-w · Cited by 45 · see citing works
The Perioperative Human Digital Twin
Lonsdale, H., Gray, G. M., Ahumada, L. M., Yates, H. M., Varughese, A., & Rehman, M. A. (2022) · Anesthesia & Analgesia · doi:10.1213/ane.0000000000005916 · Cited by 44 · see citing works
Digital twins: potentials, ethical issues and limitations
Helbing, D., & Sánchez–Vaquerizo, J. A. (2023) · Edward Elgar Publishing eBooks · doi:10.4337/9781800887374.00013 · Cited by 67 · see citing works
Hong, G.-S., Jang, M., Kyung, S., Cho, K., Jeong, J., Lee, G. Y., Shin, K., Kim, K., Ryu, S. M., Seo, J. B., et al. (2023) · Korean Journal of Radiology · doi:10.3348/kjr.2023.0393 · Cited by 45 · see citing works
Pronost, G., Mayer, F., Camargo, M., & Dupont, L. (2024) · Digital Twin · doi:10.12688/digitaltwin.17807.2 · Cited by 44 · see citing works
Naughton, M. R., Salmon, P. M., Compton, H. R., & McLean, S. G. (2024) · Frontiers in Sports and Active Living · doi:10.3389/fspor.2024.1332427 · Cited by 43 · see citing works
Job Shop Scheduling Based on Digital Twin Technology: A Survey and an Intelligent Platform
Yu, H., Han, S., Yang, D., Wang, Z., & Feng, W. (2021) · Complexity · doi:10.1155/2021/8823273 · Cited by 43 · see citing works
Liu, L., Guo, Y. G., Yin, W., Lei, G., & Zhu, J. G. (2022) · Energies · doi:10.3390/en15176186 · Cited by 42 · see citing works
Abdelaal, Y., Aupetit, M. J. M., Baggag, A., & Al‐Thani, D. (2024) · Journal of Medical Internet Research · doi:10.2196/53863 · Cited by 45 · see citing works
Sharotry, A., Jimenez, J. A., Mediavilla, F. A. M., Wierschem, D. C., Koldenhoven, R. M., & Valles, D. (2022) · IEEE Access · doi:10.1109/access.2022.3145984 · Cited by 39 · see citing works
Lauer-Schmaltz, M. W., Cash, P. J., Hansen, J. P., & Das, N. (2024) · IEEE Access · doi:10.1109/access.2024.3508029 · Cited by 41 · see citing works
Digital twins in healthcare: Applications, technologies, simulations, and future trends
Elaziz, M. A., Al‐qaness, M. A. A., Dahou, A., Al‐Betar, M. A., Mohamed, M. M., El‐Shinawi, M., Ali, A., & Ewees, A. A. (2024) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi:10.1002/widm.1559 · Cited by 37 · see citing works
Human digital twins unlocking Society 5.0? Approaches, emerging risks and disruptions
Fontes, C., Carpentras, D., & Mahajan, S. (2024) · Ethics and Information Technology · doi:10.1007/s10676-024-09787-1 · Cited by 35 · see citing works
Oulefki, A., Amira, A., & Foufou, S. (2025) · Health and Technology · doi:10.1007/s12553-025-00947-x · Cited by 36 · see citing works
Model-driven engineering for digital twins: a systematic mapping study
Lehner, D., Zhang, J., Pfeiffer, J., Sint, S., Splettstößer, A.-K., Wimmer, M., & Wortmann, A. (2025) · Software & Systems Modeling · doi:10.1007/s10270-025-01264-7 · Cited by 36 · see citing works
Edge-assisted human-to-virtual twin connectivity scheme for human digital twin frameworks
Okegbile, S. D., & Cai, J. (2022) · IEEE Vehicular Technology Conference · doi:10.1109/vtc2022-spring54318.2022.9860619 · Cited by 35 · see citing works
Metaverse and microorganism digital twins: A deep transfer learning approach
Jamshidi, M. B., Sargolzaei, S., Foorginezhad, S., & Moztarzadeh, O. (2023) · Applied Soft Computing · doi:10.1016/j.asoc.2023.110798 · Cited by 34 · see citing works
Human Digital Twin, the Development and Impact on Design
Song, Y. (2023) · Journal of Computing and Information Science in Engineering · doi:10.1115/1.4063132 · Cited by 34 · see citing works
Privacy and Security Issues for Human Digital Twins
Sirigu, G., Carminati, B., & Ferrari, E. (2022) · IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA) · doi:10.1109/tps-isa56441.2022.00011 · Cited by 35 · see citing works
Manickam, S., Yarlagadda, L., Gopalan, S. P., & Chowdhary, C. L. (2023) · IEEE Access · doi:10.1109/access.2023.3338530 · Cited by 33 · see citing works
Digital twins for well-being: an overview
Ferdousi, R., Laamarti, F., Hossain, M. A., Yang, C., & Saddik, A. E. (2022) · Digital Twin · doi:10.12688/digitaltwin.17475.2 · Cited by 32 · see citing works
A meta-model for modular composition of tailored human digital twins in production
Montini, E., Bettoni, A., Ciavotta, M., Carpanzano, E., & Pedrazzoli, P. (2021) · Procedia CIRP · doi:10.1016/j.procir.2021.11.116 · Cited by 26 · see citing works
Survey on digital twins for natural environments: A communication network perspective
Maimour, M., Ahmed, A., & Rondeau, É. (2024) · Internet of Things · doi:10.1016/j.iot.2024.101070 · Cited by 34 · see citing works
A Real-Time Cross-Domain Wi-Fi-Based Gesture Recognition System for Digital Twins
Su, J. D., Mao, Q., Liao, Z., Sheng, Z., Huang, C., & Zhang, X. (2023) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2023.3310073 · Cited by 28 · see citing works
Digital twins in sport: Concepts, taxonomies, challenges and practical potentials
Hliš, T., Fister, I., & Fister, I. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.125104 · Cited by 27 · see citing works
Digital Twins and Cyber-Physical Systems: A New Frontier in Computer Modeling
Vidyalakshmi, G. V., Gopikrishnan, S., Boulila, W., Koubâa, A., & Srivastava, G. (2025) · Computer Modeling in Engineering & Sciences · doi:10.32604/cmes.2025.057788 · Cited by 34 · see citing works
Digital Twin-Driven Intelligent Construction: Features and Trends
Zhang, H., Zhou, Y., Zhu, H., Šumarac, D. M., & Cao, M. (2021) · Structural durability & health monitoring · doi:10.32604/sdhm.2021.018247 · Cited by 28 · see citing works
Human Digital Twin: A SurveyPreprint
Lin, Y., Chen, L., Ali, A., Nugent, C., Cleland, I., Li, R., Gao, D., Wang, H., Wang, Y., & Ning, H. (2022) · Research Square · doi:10.21203/rs.3.rs-2369073/v1 · Cited by 27 · see citing works
Edge AI-Enabled Road Fixture Monitoring System
Heravi, M. Y., Dola, I. S., Jang, Y., & Jeong, I. (2024) · Buildings · doi:10.3390/buildings14051220 · Cited by 26 · see citing works
Posture-Invariant Three Dimensional Human Hand Statistical Shape Model
Yang, Y., Yuan, T., Huysmans, T., Elkhuizen, W. S., Tajdari, F., & Song, Y. (2020) · Journal of Computing and Information Science in Engineering · doi:10.1115/1.4049445 · Cited by 24 · see citing works
Maïzi, Y., Arcand, A., & Bendavid, Y. (2024) · Internet of Things · doi:10.1016/j.iot.2024.101379 · Cited by 23 · see citing works
Elaboration of Innovative Digital Twin Models for Healthcare Monitoring With 6G Functionalities
Brahmi, R., Boujnah, N., & Ejbali, R. (2024) · IEEE Access · doi:10.1109/access.2024.3439269 · Cited by 22 · see citing works
Design of Digital Twin Sensing Strategies Via Predictive Modeling and Interpretable Machine Learning
Kapteyn, M. G., & Willcox, K. E. (2022) · Journal of Mechanical Design · doi:10.1115/1.4054907 · Cited by 22 · see citing works
From digital control to digital twins in medicine: A brief review and future perspectives
Eftimie, R., Mavrodin, A., & Bordas, S. (2022) · Advances in applied mechanics · doi:10.1016/bs.aams.2022.09.001 · Cited by 24 · see citing works
Sheng, B., Wang, Z., Qiao, Y., Xie, S. Q., Tao, J., & Duan, C. (2023) · Digital Health · doi:10.1177/20552076231203672 · Cited by 25 · see citing works
Seeking a Definition of Digital Twins for Construction and Infrastructure Management
Aragón, A., Arquier, M., Tokdemir, O. B., Enfedaque, A., Alberti, M. G., Lieval, F., Loscos, E., Pavón, R. M., Novischi, D., Legazpi, P. V., et al. (2025) · Applied Sciences · doi:10.3390/app15031557 · Cited by 24 · see citing works
Digital Twins About Humans—Design Objectives From Three Projects
Bomström, H., Annanperä, E., Kelanti, M., Xu, Y., Mäkelä, S.-M., Immonen, M., Siirtola, P., Teern, A., Liukkunen, K., & Päivärinta, T. (2022) · Journal of Computing and Information Science in Engineering · doi:10.1115/1.4054270 · Cited by 21 · see citing works
Workforce Learning Curves for Human-Based Assembly Operations: A State-of-the-Art Review
Peña, C., Romero, D., & Noguez, J. (2022) · Applied Sciences · doi:10.3390/app12199608 · Cited by 19 · see citing works
Digital twins in cardiovascular disease: a scoping review
Zou, H., Zheng, X., Wu, L., Zhang, S., Chang, P., & Chen, Y. (2025) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2025.106138 · Cited by 17 · see citing works
IoT-enabled model for Digital Twin Of Mental Stress (DTMS)
Ferdousi, R., Hossain, M. A., & Saddik, A. E. (2021) · IEEE Globecom Workshops (GC Wkshps) · doi:10.1109/gcwkshps52748.2021.9681996 · Cited by 17 · see citing works
Cappelletti, L., Fontana, T., Donato, G. W. D., Tucci, L. D., Casiraghi, E., & Valentini, G. (2020) · Computers · doi:10.3390/computers9020037 · Cited by 17 · see citing works
Self-citationPronost, G., Mayer, F., Camargo, M., & Dupont, L. (2023) · Digital Twin · doi:10.12688/digitaltwin.17807.1 · Cited by 64 · see citing works
Lehmann, J., Granrath, L., Browne, R., Ogawa, T., Kokubun, K., Taki, Y., Jokinen, K., Janböcke, S., Lohr, C., Wieching, R., et al. (2024) · Sustainability · doi:10.3390/su16073064 · Cited by 16 · see citing works
Extension of HAAS for the Management of Cognitive Load
Eesee, A. K., Jaskó, S., Eigner, G., Abonyi, J., & Ruppert, T. (2024) · IEEE Access · doi:10.1109/access.2024.3359902 · Cited by 15 · see citing works
Xue, Y., Zhang, B., Su, K., Li, Y., Zhu, H., & Pan, H. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.110940 · Cited by 16 · see citing works
- Authors
- Barricelli, B. R., Casiraghi, E., Gliozzo, J., Petrini, A., & Valtolina, S.
- Affiliations
- University of Brescia (IT)
- University of Milan (IT)
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico (IT)
- Venue
- IEEE Access
- Published
- 2020
- Volume
- 8
- Pages
- 26637-26664
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W3004825562
- Cited by
- 259
- References
- 114
- Citations by year
- 2026: 24 · 2025: 58 · 2024: 60 · 2023: 36 · 2022: 47 · 2021: 26 · 2020: 8
- FWCI
- 18.65
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- IEEE Access (publishedVersion, cc-by)
- Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Institutional Research Information System (Università degli Studi di Brescia) (submittedVersion, other-oa)
- Funders
- Bando Sostegno alla Ricerca 2019 through the University of Milan
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Keywords
- human digital twin, wearable sensors, Internet of Things, dynamic data, dietary monitoring, sleep monitoring, activity monitoring
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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