Zhu, Enshen et Yang, Sheng.
2025.
« Advancing human digital twin: A mini review of human modelling ».
In Proceedings of the CSME-CFDSC-CSR 2025 International Congress (Montreal, QC, Canada, May 25-28, 2025)
Coll. « Progress in Canadian Mechanical Engineering », vol. 8.
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Résumé
The human digital twin (HDT) represents a comprehensive digital counterpart of an individual, integrating biophysical, cognitive, psychological, and social attributes. The concept of HDT comes from the conventional digital twin used in industrial engineering. Its application extends into personalized healthcare, smart manufacturing, and human-centered systems. This paper reviews the evolution of human modelling, from early physical representations to modern digital simulations, leading to the development of HDT. A key focus is unified HDT information modelling, consolidating diverse human attributes into an integrated information model. The paper categorizes essential HDT components, including physical, mental, psychological, ability, activity, and social-connection models. Additionally, This paper highlights challenges such as data and software standardization, privacy concerns, technical limitations, and the complexity of modelling dynamic human characteristics. Addressing these challenges will be crucial for advancing HDT applications in industry and healthcare. Future research directions include exploring data collection and simulation methods to empower the HDT functions in real-world applications.
| Type de document: | Compte rendu de conférence |
|---|---|
| Éditeurs: | Éditeurs ORCID Hof, Lucas A. NON SPÉCIFIÉ Di Labbio, Giuseppe NON SPÉCIFIÉ Tahan, Antoine NON SPÉCIFIÉ Sanjosé, Marlène NON SPÉCIFIÉ Lalonde, Sébastien NON SPÉCIFIÉ Demarquette, Nicole R. NON SPÉCIFIÉ |
| Date de dépôt: | 18 déc. 2025 15:34 |
| Dernière modification: | 18 déc. 2025 15:34 |
| URI: | https://espace2.etsmtl.ca/id/eprint/32532 |
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