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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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Chomski, O. (2025) · AI & Society · doi:10.1007/s00146-025-02691-2 · Cited by 2
Comparative analysis on AI-driven human digital twin for personalized and predictive medicine
Din, G. M., Shams, M. U., Rahmani, A. N., Rehman, A., Ahmed, M. M., & Shoukat, M. A. (2025) · Journal of Clinical Practice and Medical Research · doi:10.59324/jcpmr.2025.1(1).06 · Cited by 3
Lyu, S., Lim, K. Y. H., Chen, C., Youcef‐Toumi, K., & Yang, X. J. (2026) · Computers in Industry · doi:10.1016/j.compind.2026.104463 · Cited by 2
Human digital twins in sports and rehabilitation: a systematic review
Barricelli, B. R., Cerutti, F., & Morzenti, S. (2026) · Behaviour and Information Technology · doi:10.1080/0144929x.2026.2660222 · Cited by 2
Self-citationShah, S. T. A., Santos, J. P. O., Constantinescu, G., Fernandes, J. M., & Pereira, A. B. (2026) · International Conference on Information and Computer Technologies (ICICT) · doi:10.1145/3803291.3803295 · Cited by 2
“Barricelli et al. [2] proposed a Human Digital Twin for fitness management, combining IoT sensors (wearables) and contextual user input (e.g., mood and diet) to provide personalized training recommendations.”
How gender is intertwined with robots and affective technologies: A short review
Mavridis, N. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-821392-6.00010-8 · Cited by 2
Automated Personnel Digital Twinning in Industrial Workplaces
Massiris, M., Delrieux, C. A., & Munoz, J. A. F. (2022) · International Conference on Electrical, Computer and Energy Technologies (ICECET) · doi:10.1109/icecet55527.2022.9872882 · Cited by 2
“Mostly devised for devices, facilities, machinery in manufacturing, automotive industries, healthcare, and urban planning, recently a growing interest arose in human twinning, for instance in sports performance analysis [2].”
BackgroundConstruction of scientific fitness guidance model based on IoT technology
Yang, X. (2024) · Multimedia Tools and Applications · doi:10.1007/s11042-024-18547-8 · Cited by 2
“Integrated with Smart Fit, a software system, the entire participant team is interconnected, enabling coaches and trainers to efficiently monitor and oversee individual fitness activities and outcomes [20].”
An Investigation into the Rise of Wearable Technologies in the Healthcare Sector
Sharma, A., Bijo, K., Manandhar, S. P., & Sharma, L. K. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-60428-7_15 · Cited by 3
Peña, C., Romero, D., & Noguez, J. (2024) · Computers & Industrial Engineering · doi:10.1016/j.cie.2024.110314 · Cited by 2
Human Digital Twins: Efficient Privacy-Preserving Access Control Through Views Pre-materialisation
Sirigu, G., Carminati, B., & Ferrari, E. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-65172-4_2 · Cited by 2
Sağlık Hizmetlerinde Çığır Açan Uygulamalar: İnsan Dijital İkizi ile Geleceğe Yolculuk
Özsezer, G., & Mermer, G. (2024) · Bandırma Onyedi Eylül Üniversitesi Sağlık Bilimleri ve Araştırmaları Dergisi · doi:10.46413/boneyusbad.1440963 · Cited by 3
The better ones: the rise of human digital twins—our future or our demise?
Kabalska, A., & Wagner, R. (2025) · Future Business Journal · doi:10.1186/s43093-025-00582-y · Cited by 2
“A few of the many non-industrial applications for digital twins include healthcare [29] and well-being [1], education [14], and fashion [30].”
Extrapolation of weight from smart scale data
Caballero, P., Ortega, J. A., & González-Abril, L. (2021) · Procedia Computer Science · doi:10.1016/j.procs.2021.09.046 · Cited by 2
“The latest Internet of Things (IoT) developments [3] focused on the fitness provides to the market a sort of commercial ubiquitous devices [7], in particular smart bands and smart watches.”
BackgroundAbadía, J. J. P., & Smarsly, K. (2022) · Intelligent systems reference library · doi:10.1007/978-3-030-97516-6_1 · Cited by 2
Current Status and Future Perspective of the Human Digital Twin
Tada, M., Endo, Y., & Maruyama, T. (2022) · Journal of the Robotics Society of Japan · doi:10.7210/jrsj.40.579 · Cited by 2
Construction Method and Application Prospect of Electrical Machine Digital Twin
Liu, L., Guo, Y. G., Lei, G., Yin, W., Ba, X., & Zhu, J. G. (2022) · International Conference on Electrical Machines and Systems (ICEMS) · doi:10.1109/icems56177.2022.9983289 · Cited by 2
“Then, medical industry and urban construction have successively introduced the DT technology for human health tracking and decision-making [5,6].”
BackgroundHtet, H., Usman, I., & Anshori, M. Y. (2023) · Business and Finance Journal · doi:10.33086/bfj.v8i1.3662 · Cited by 2
“Several possible use domains have already been identified, including fitness, (Barricelli et al., 2020) simulations of viral infections, and promoting healthy lifestyles in smart cities.”
BackgroundAbinaya, P., Kumar, S. P., Sivaprakash, P., Kumar, K. A., Shuriya, B., & Khan, S. B. (2024) · doi:10.1002/9781394195336.ch11 · Cited by 2
NEFT-QAZ SƏNAYESİ ÜÇÜN RƏQƏMSAL ƏKİZLƏRİN KONSEPTUAL MODELİ
İmamverdiyev, Y. (2020) · Problems of Information Technology · doi:10.25045/jpit.v11.i2.04 · Cited by 1
A Patent Review of Lung-airway Modeling with Tangential Digital Twin Technology
Bao, Y., Li, X., Zhao, Y., & Qu, S. (2022) · Recent Patents on Engineering · doi:10.2174/1872212116666220309122112 · Cited by 1
Basic Research on Laborer State Prediction Towards the Realization of Human Digital Twin
Watanabe, R., Takihara, Y., Matsuno, K., & TANIMIZU, Y. (2024) · IFIP advances in information and communication technology · doi:10.1007/978-3-031-65894-5_8 · Cited by 1
Nomura, M., & Nakao, A. (2024) · IEICE Communications Express · doi:10.23919/comex.2024xbl0143 · Cited by 1
21st-Century Alienation: From Engineered Humans to Predicted Humans
Chiodo, S. (2025) · SpringerBriefs in philosophy · doi:10.1007/978-3-031-85478-1_2 · Cited by 1
Towards Digital Twin for Human Skeleton in Smart Manufacturing with Predictive Modelling
Song, X., He, X., Li, Z., Song, H., Lin, H., & Rich, M. E. (2025) · Springer eBooks · doi:10.1007/978-3-031-82170-7_7 · Cited by 1
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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