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Human Digital Twin: A Survey
December 12, 2022 ยท The Cartographer ยท ๐ Journal of Cloud Computing
"No code URL or promise found in abstract"
"Title-pattern auto-detect: Human Digital Twin: A Survey"
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Authors
Yujia Lin, Liming Chen, Aftab Ali, Christopher Nugent, Cleland Ian, Rongyang Li, Dazhi Gao, Hang Wang, Yajie Wang, Huansheng Ning
arXiv ID
2212.05937
Category
cs.HC: Human-Computer Interaction
Citations
69
Venue
Journal of Cloud Computing
Last Checked
1 day ago
Abstract
Digital twin has recently attracted growing attention, leading to intensive research and applications. Along with this, a new research area, dubbed as "human digital twin" (HDT), has emerged. Similar to the conception of digital twin, HDT is referred to as the replica of a physical-world human in the digital world. Nevertheless, HDT is much more complicated and delicate compared to digital twins of any physical systems and processes, due to humans' dynamic and evolutionary nature, including physical, behavioral, social, physiological, psychological, cognitive, and biological dimensions. Studies on HDT are limited, and the research is still in its infancy. In this paper, we first examine the inception, development, and application of the digital twin concept, providing a context within which we formally define and characterize HDT based on the similarities and differences between digital twin and HDT. Then we conduct an extensive literature review on HDT research, analyzing underpinning technologies and establishing typical frameworks in which the core HDT functions or components are organized. Built upon the findings from the above work, we propose a generic architecture for the HDT system and describe the core function blocks and corresponding technologies. Following this, we present the state of the art of HDT technologies and applications in the healthcare, industry, and daily life domain. Finally, we discuss various issues related to the development of HDT and point out the trends and challenges of future HDT research and development.
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