The Internet of things (IoT) can significantly enhance the quality of human
life, specifically in healthcare, attracting extensive attentions to
IoT-healthcare services. Meanwhile, the human digital twin (HDT) is proposed as
an innovative paradigm that can comprehensively characterize the replication of
the individual human body in the digital world and reflect its physical status
in real time. Naturally, HDT is envisioned to empower IoT-healthcare beyond the
application of healthcare monitoring by acting as a versatile and vivid human
digital testbed, simulating the outcomes and guiding the practical treatments.
However, successfully establishing HDT requires high-fidelity virtual modeling
and strong information interactions but possibly with scarce, biased and noisy
data. Fortunately, a recent popular technology called generative artificial
intelligence (GAI) may be a promising solution because it can leverage advanced
AI algorithms to automatically create, manipulate, and modify valuable while
diverse data. This survey particularly focuses on the implementation of
GAI-driven HDT in IoT-healthcare. We start by introducing the background of
IoT-healthcare and the potential of GAI-driven HDT. Then, we delve into the
fundamental techniques and present the overall framework of GAI-driven HDT.
After that, we explore the realization of GAI-driven HDT in detail, including
GAI-enabled data acquisition, communication, data management, digital modeling,
and data analysis. Besides, we discuss typical IoT-healthcare applications that
can be revolutionized by GAI-driven HDT, namely personalized health monitoring
and diagnosis, personalized prescription, and personalized rehabilitation.
Finally, we conclude this survey by highlighting some future research
directions.

物联网、医疗、人类数字孪生、生成式人工智能、物联网医疗是研究的关键词，本文重点介绍了生成式人工智能驱动的人类数字孪生在物联网医疗领域的应用和实现方法，包括数据获取、通信、管理、数字建模和数据分析等方面，以及个性化健康监测、诊断、处方和康复等典型物联网医疗应用，并探讨了未来的研究方向。

物联网健康中的生成式人工智能驱动人体数字仿真：一项综合调查

Generative AI-Driven Human Digital Twin in IoT-Healthcare: A  Comprehensive Survey

Mobile Artificial Intelligence-Generated Content (AIGC) technology refers to
the adoption of AI algorithms deployed at mobile edge networks to automate the
information creation process while fulfilling the requirements of end users.
Mobile AIGC has recently attracted phenomenal attentions and can be a key
enabling technology for an emerging application, called human digital twin
(HDT). HDT empowered by the mobile AIGC is expected to revolutionize the
personalized healthcare by generating rare disease data, modeling high-fidelity
digital twin, building versatile testbeds, and providing 24/7 customized
medical services. To promote the development of this new breed of paradigm, in
this article, we propose a system architecture of mobile AIGC-driven HDT and
highlight the corresponding design requirements and challenges. Moreover, we
illustrate two use cases, i.e., mobile AIGC-driven HDT in customized surgery
planning and personalized medication. In addition, we conduct an experimental
study to prove the effectiveness of the proposed mobile AIGC-driven HDT
solution, which shows a particular application in a virtual physical therapy
teaching platform. Finally, we conclude this article by briefly discussing
several open issues and future directions.

移动人工智能生成内容（AIGC）技术是指在移动边缘网络上采用 AI 算法自动化信息创建过程，并满足最终用户要求的一种技术。移动 AIGC 近期引起了巨大关注，可以成为一种关键的新兴应用技术，称为人类数字孪生 (HDT)。移动 AIGC 赋能的 HDT 有望通过生成罕见疾病数据、建模高保真数字孪生、构建多功能试验台和提供全天候定制医疗服务，从而彻底改变个性化医疗。在本文中，我们提出了移动 AIGC 驱动的 HDT 系统架构，并强调了相应的设计要求和挑战。此外，我们还介绍了两个使用案例：定制手术规划和个性化药物。此外，我们进行了一项实验研究，证明了所提出的移动 AIGC 驱动的 HDT 解决方案的有效性，在虚拟物理疗法教学平台中找到了特定应用。最后，我们简要讨论了几个未解决的问题和未来发展方向。