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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 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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Cites
Cortes, C., & Vapnik, V. (1995) · Machine Learning · doi:10.1007/bf00994018 · Cited by 59,421
(2008) · Journal of Machine Learning Research · Cited by 33,051
(1992) · Cited by 23,431
Use of Ranks in One-Criterion Variance Analysis
Kruskal, W. H., & Wallis, W. A. (1952) · Journal of the American Statistical Association · doi:10.1080/01621459.1952.10483441 · Cited by 13,912
(1973) · CERN Document Server (European Organization for Nuclear Research) · Cited by 12,895
He, H., & Garcia, E. A. (2009) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2008.239 · Cited by 10,359
Practical Bayesian Optimization of Machine Learning Algorithms
Snoek, J., Larochelle, H., & Adams, R. P. (2012) · arXiv · doi:10.48550/arxiv.1206.2944 · Cited by 6,691
Top 10 algorithms in data mining
Wu, X., Kumar, V., Ross Quinlan, J., Ghosh, J., Yang, Q., Motoda, H., McLachlan, G. J., Ng, A., Liu, B., Yu, P. S., et al. (2008) · Knowledge and Information Systems · doi:10.1007/s10115-007-0114-2 · Cited by 5,667
An Introduction to Kernel and Nearest-Neighbor Nonparametric Regression
Altman, N. (1992) · The American Statistician · doi:10.1080/00031305.1992.10475879 · Cited by 5,657
XV.—The Correlation between Relatives on the Supposition of Mendelian Inheritance.
Fisher, R. A. (1919) · Transactions of the Royal Society of Edinburgh · doi:10.1017/s0080456800012163 · Cited by 4,387
Research works printed but not linked: 19
- 2019, The Living Heart Project
- holtmannspotter, 2017, Simulation in clinical practice: First experience with Sim&Cure before implantation of flow diverter (pipeline) or Web-device for the treatment of intracranial aneurysm, Proc ABC/WIN
- 2015, Data-Driven Treatments as Unique as Your Own Body
- 2019, What is Precision Medicine?
- scharff, 2010, From Digital Twin to Improved Patient Experience Siemens Healthineers
- polyniak, 2016, The Johns Hopkins Hospital Launches Capacity Command Center to Enhance Hospital Operations John Hopkins Medicine
- 0, Network modeling of patients’ biomolecular profiles for clinical phenotype/outcome prediction, Sci Rep
- merz, 1998, UCI Repository of Machine Learning Datasets
- 10.1007/BF00116835 · DOI
- karegowda, 2012, Cascading K-means clustering and K-nearest neighbor classifier for categorization of diabetic patients, Int J Eng Adv Technol, 1, 147
- watcher, 2017, Counterfactual explanations without opening the black box: Automated decisions and the GDPR, arXiv 1711 00399
- wang, 2015, Or’s of and’s for interpretable classification, with application to context-aware recommender systems, arXiv 1504 07614
- mitchell, 1997, Machine Learning
- ribeiro, 2018, High-precision model-agnostic explanations, Proc AAAI Conf Artif Intell (AAAI)
- 2020, The Ill-Fated Space Odyssey of Apollo 13
- 10.1007/s12652-018-0953-6 · DOI
- 10.2307/2286009 · DOI · Paper page
- 10.2307/2280779 · DOI
- molnar, 2019, Interpretable Machine Learning A Guide for Making Black Box Models Explainable
Cited by
Sorted by citations
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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
Rathore, M. M., Shah, S. A., Shukla, D., Bentafat, E., & Bakiras, S. (2021) · IEEE Access · doi:10.1109/access.2021.3060863 · Cited by 616
“[133] focuses on fitness-related measurements of athletes.”
BackgroundPham, 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
Stepin, I., Alonso, J. M., Catala, A., & Pereira-Farina, M. (2021) · IEEE Access · doi:10.1109/access.2021.3051315 · Cited by 376
“Thus, the outlined classification-oriented frameworks are evaluated on classifiers based on logistic regression [55], [136], [153], [158], decision trees [46], [80], [122], [140], [150], [155], [159], gradient boosted decision trees [147], support vector machines [131], [138], [146], random forests [81], [86], [142]–[…”
BackgroundMethodA 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
Chen, J., Yi, C., Okegbile, S. D., Cai, J., & Shen, X. (2023) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2023.3308717 · Cited by 284
“To deal with this, the data imputation technique – a technique that replaces all missing data based on the structure of the underlying datasets – has been demonstrated to be an effective solution [169].”
BackgroundMethodDigital 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
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 263
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
“The missing values can be estimated using the KNN-imputation technique [12].”
BackgroundMethodExploring 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
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Hassani, H., Huang, X., & MacFeely, S. (2022) · Big Data and Cognitive Computing · doi:10.3390/bdcc6030083 · Cited by 206
“…have been widely applied in coaching physical activities [74], giving personalized and precise nutrition advice [75], assisting with fitness management [76], and improving self-management of ergonomic risks [77], all thanks to advances in sensors, smart devices, and expanding IoT infrastructures.”
BackgroundLattanzi, L., Raffaeli, R., Peruzzini, M., & Pellicciari, M. (2021) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2021.1911003 · Cited by 205
“Several research works can be found in literature, addressing ideas and challenges related to the creation of digital copies of human beings (Truby and Brown 2021; Barricelli et al. 2020).”
BackgroundThe 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 217
“This can help athletes and coaches develop more effective training plans and prevent injuries [60]; • Workplace safety: Human digital twins can be used to improve workplace safety by simulating and predicting how an individual will respond to different work environments and hazards.”
BackgroundDigital 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
“For athletes monitoring, Barricelli et al. [18] proposed a DT framework for giving predictions and suggestions and then optimizing the behavior of the athletes, where SmartFit integrating sensors embedded in the portable devices was developed for continuous data collection.”
BackgroundHu, 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 189
“The bones and muscle model of the digital human can be utilized to prevent injury [49].”
MethodDigital 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 211
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
“have proposed in [11] the integration of digital twin techThe use of 360° cameras is motivated by immersive user viewing, which enables a richer and more”
MethodAsad, U., Khan, M., Khalid, A., & Lughmani, W. A. (2023) · Sensors · doi:10.3390/s23083938 · Cited by 187
“As a high-level numerical computing platform, MATLAB is used in a number of studies involving DTs in the medical domain [70,74,75], as further discussed in the applications.”
MethodDigital 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
“The model can alert the patient for doctor consultation and changes in medicine and food habits.(13)”
BackgroundA 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
“, nutrition information) into tracking applications (Barricelli et al. 2020).”
BackgroundInfluentialGenerative-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 168
“…its application in security and privacy schemes, as summarized in Table VI. Traditional data imputation methods, such as K -nearest neighbors-based [92] and deep-learning-based imputation [93], often rely on existing observed data for modeling and prediction, and cannot directly generate new data…”
MethodApplication of Digital Twins in multiple fields
Guo, J., & Lv, Z. (2022) · Multimedia Tools and Applications · doi:10.1007/s11042-022-12536-5 · Cited by 151
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
“It is worth mentioning that, although the majority of [18], [19], [20], [21], and [22] discussed the importance of connectivity in HDT, none of these works delved into investigating and modelling this connectivity scheme.”
BackgroundMethodIntelligent Wearable Systems: Opportunities and Challenges in Health and Sports
Yang, L., Amin, O., & Shihada, B. (2024) · ACM Computing Surveys · doi:10.1145/3648469 · Cited by 159
Xames, M. D., & Topcu, T. G. (2024) · IEEE Access · doi:10.1109/access.2023.3349379 · Cited by 139
“For example, they delve into the intricate aspects of crafting hardware [98], [99] or software, including formulation of algorithms [100], [101] that are essential for DTs. Additionally, certain instances involve the exploration and development of DT prototypes [102], [103], [104].”
BackgroundMethodMykoniatis, K., & Harris, G. A. (2021) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-020-01724-5 · Cited by 117
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 126
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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
“Barricelli et al. [7] studied HDTs of a sports team, which could monitor and manage athletes by collecting measurements describing their behavior.”
BackgroundInfluentialSurvey 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
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
“…digital twin city (DTC) model that integrates multimodal data (physiological sensing, visual sensing) on environmental demands in urban communities [66] Intelligent traffic management based on digital twin (1) The digital twin technology can identify and optimize the regional road conditions and…”
BackgroundA 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
Newrzella, S. R., Franklin, D. W., & Haider, S. (2021) · IEEE Access · doi:10.1109/access.2021.3115055 · Cited by 100
“Further application domains so far addressed by research are for example Construction [37], [52]–[54], Healthcare [55]–[60], Oil and Gas Industry [61]–[65], and Logistics [19], [66]–[68].”
BackgroundDrummond, D., & Gonsard, A. (2024) · Journal of Medical Internet Research · doi:10.2196/58504 · Cited by 95
“On the other hand, digital twins corresponding to real-time representations of patients through home-based data collection via wearable, using machine learning techniques for analysis and alert detection [29,31].”
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
“An H-DT is used to treat physical [15] or psychological [16] ailments better as well as to control athletes training intensity [17].”
MethodCasiraghi, E., Malchiodi, D., Trucco, G., Frasca, M., Cappelletti, L., Fontana, T., Esposito, A. A., Avola, E., Jachetti, A., Reese, J., et al. (2020) · IEEE Access · doi:10.1109/access.2020.3034032 · Cited by 81
“Given the promising results achieved by studies exploiting Artificial Intelligence (AI) and/or probabilistic models for outcome prediction [2]–[4] in bio-medical problems where”
BackgroundSelf-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
“…leg raise Pilate dips Push-up Side-to-side lunge Wall push-up 1 h workout 10 exercises 3 sets p/ exercise 1–2 min. rest N = 10 S: both A: 25.9 ± 3.21 Barricelli et al. (2020) [39] Wristband FitBit Charge HR Commercial n.d. n.d. n.d. P2P n.d. Offline Heart rate number of steps per day physical…”
InfluentialPapyshev, G., & Yarime, M. (2021) · Data & Policy · doi:10.1017/dap.2021.17 · Cited by 81
“Some pilot projects have focused on creating human DTs with the usage of wearable fitness bracelets SmartFit, through which the behavioral data about activities, food consumption, and mood has been aggregated (Barricelli et al., 2020).”
BackgroundMetaverse and Personal Healthcare
Song, Y.-T., & Qin, J. (2022) · Procedia Computer Science · doi:10.1016/j.procs.2022.10.136 · Cited by 79
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 86
“Still, these primarily focus on using conventional IoT sensors to collect human information, similar to DT approaches in healthcare, such as fitness management [116] and disease diagnosis [114].”
BackgroundHuman 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
Digital Twins for Healthcare Using Wearables
Johnson, Z., & Saikia, M. J. (2024) · Bioengineering · doi:10.3390/bioengineering11060606 · Cited by 74
“This has been used as a method to track movements during exercise for a group of athletes wearing smart clothes and to create a digital twin that records the athletes’ movements [51].”
MethodSustainable 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
“, human DT [6], DT city [7], and DT automation [8].”
BackgroundRoadmap 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
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 78
“In contexts such as sports, for example, where the goal is to maintain athlete performance, prevent injuries, and respond proactively, DTs combine variables (such as sleep hours, caloric intake, heart rate, etc.) with Machine Learning (ML) techniques to generate personalized and adaptive plans [63].”
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
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
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 58
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
“Only recently the idea of adopting DTs to build a human replicas has been investigated both as general concept in [26] and in specific domains such as industrial training [27], health [28], fitness [29] and ambient assisted living [30].”
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
“Nowadays, digital twins are being made for almost all physical things, including humans [12], [13], cars [14], [15], water systems [16], and ice cream machines [17], and even intangible entities, such as organizations [18].”
BackgroundRuiu, P., Nitti, M., Pilloni, V., Cadoni, M. I., Grosso, E., & Fadda, M. (2024) · Multimodal Technologies and Interaction · doi:10.3390/mti8060048 · Cited by 57
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
“HDTs in therapy and rehabilitation substantially extend the scope and nature of digital twin applications (Saddik, 2018), such that the human patient is seen as the physical object, which is monitored and based on whose data simulations should be done to predict and improve the treatment's outcome (Barricelli et al.,…”
BackgroundInfluentialDigital twins in healthcare IoT: A systematic review
Kabir, M. R., Shishir, F. S., Shomaji, S., & Ray, S. (2025) · High-Confidence Computing · doi:10.1016/j.hcc.2025.100340 · Cited by 68
Newrzella, S. R., Franklin, D. W., & Haider, S. (2022) · IEEE Access · doi:10.1109/access.2022.3202941 · Cited by 48
Roopa, M. S., & Venugopal, K. R. (2025) · IEEE Access · doi:10.1109/access.2025.3547991 · Cited by 56
“Barricelli et al. [118] have highlighted the significance of tracking fitness-related metrics to assess an athlete’s daily performance.”
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
“Barricelli et al. (2020) published research on managing human fitness through keeping an HDT updated by various biometric sensors.”
BackgroundAndres, 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
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 47
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 70
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 46
“Recently, several studies on DTs in medicine have been published [193-202], including a wide range of applications such as healthcare management [193], fitness [194], simulating viral infections [195], smart city well-being [196], remote surgery [197], and cardiovascular diseases [200-202].”
BackgroundPronost, G., Mayer, F., Camargo, M., & Dupont, L. (2024) · Digital Twin · doi:10.12688/digitaltwin.17807.2 · Cited by 44
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 53
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
Liu, L., Guo, Y. G., Yin, W., Lei, G., & Zhu, J. G. (2022) · Energies · doi:10.3390/en15176186 · Cited by 42
Abdelaal, Y., Aupetit, M. J. M., Baggag, A., & Al‐Thani, D. (2024) · Journal of Medical Internet Research · doi:10.2196/53863 · Cited by 49
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
Lauer-Schmaltz, M. W., Cash, P. J., Hansen, J. P., & Das, N. (2024) · IEEE Access · doi:10.1109/access.2024.3508029 · Cited by 41
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
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
“HDTs require enormous power computing capacity and the deployment of hardware to create ubiquitous sensing environments (Barricelli et al., 2020).”
InfluentialOulefki, A., Amira, A., & Foufou, S. (2025) · Health and Technology · doi:10.1007/s12553-025-00947-x · Cited by 36
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
“…be the reason for the very low number of occurrences of DTs representing processes, and the lack of applications of automation techniques to DTs representing biological beings, even though there are already discussions, outlined challenges, and experiences reported for such DTs [6, 13, 20, 50].”
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
“Thus, a seamless humantwin connection may not always be guaranteed [4].”
BackgroundMethodMetaverse 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 40
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 41
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
“For instance, [20] provides a fitness application of HDTs with which the coach can monitor the athlete’s conditions and behaviour, aiming to increase their performance and health conditions.”
BackgroundManickam, S., Yarlagadda, L., Gopalan, S. P., & Chowdhary, C. L. (2023) · IEEE Access · doi:10.1109/access.2023.3338530 · Cited by 35
“A group of HDTs was created in [33] for an athletic team.”
BackgroundA 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
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
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
“Barricelli et al. [28] use wearable sensors to collect the athlete’s fitness-related data to build the athlete’s DT, and analyze it in the DT system to dynamically predict the health status of athlete and give suggestions.”
BackgroundDigital 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 37
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
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
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
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 27
“…and has been applied for various purposes, such as monitoring, management, maintenance, optimization, and prediction in several industries, including agriculture [37], healthcare [38], sport and fitness [39], construction and smart cities [40,41], and bridge infrastructure monitoring [12].”
BackgroundPosture-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 27
“Recently, the human integration in the digital twin has received increased attention in many applications [3], e.g. for empowering operators [4], monitoring and managing athletes’ fitness activity and results [5], personalized product design [6].”
BackgroundMaïzi, Y., Arcand, A., & Bendavid, Y. (2024) · Internet of Things · doi:10.1016/j.iot.2024.101379 · Cited by 23
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
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
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
Sheng, B., Wang, Z., Qiao, Y., Xie, S. Q., Tao, J., & Duan, C. (2023) · Digital Health · doi:10.1177/20552076231203672 · Cited by 31
“Athletes and bodybuilders can use DT to accurately judge whether exercise posture is standard and scientifically calculate the amount of training to achieve the best effect.(21) Another critical issue for personalized DT is its potential privacy and ethical implications.”
BackgroundSeeking 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
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
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
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
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
Cappelletti, L., Fontana, T., Donato, G. W. D., Tucci, L. D., Casiraghi, E., & Valentini, G. (2020) · Computers · doi:10.3390/computers9020037 · Cited by 17
Self-citationPronost, G., Mayer, F., Camargo, M., & Dupont, L. (2023) · Digital Twin · doi:10.12688/digitaltwin.17807.1 · Cited by 64
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
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
“…behaviors [22], geospatial and psychophysical conditions, contextual parameters, intentions, cognitions, emotional state, food income [23], motion recognition [10], and other biological parameters such as electromyogram (EMG), heart rate, heart rhythm, respiration, blood pressure,…”
BackgroundXue, 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 17
Digital twins for well-being: an overview
Ferdousi, R., Laamarti, F., Hossain, M. A., Yang, C., & Saddik, A. E. (2021) · Digital Twin · doi:10.12688/digitaltwin.17475.1 · Cited by 48
Metadata
- 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
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