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.

翻译：物联网可显著提升人类生活质量，尤其在医疗领域，这促使物联网医疗服务备受关注。与此同时，人体数字孪生作为一种创新范式被提出，它能够在数字世界中全面表征个体人体的复制，并实时反映其物理状态。自然而言，人体数字孪生被视为超越医疗监测应用的技术——通过充当通用而生动的人体数字化试验台，模拟治疗结果并指导临床实践。然而，成功构建人体数字孪生需要高保真虚拟建模与强信息交互，但往往面临数据稀疏、有偏且含噪声的挑战。幸运的是，近期流行的生成式人工智能技术或许能提供解决方案：其可利用先进AI算法自动创建、操控并生成具有价值的多样化数据。本综述聚焦于物联网医疗中生成式AI驱动的人体数字孪生实现。我们首先阐述物联网医疗背景及生成式AI驱动的人体数字孪生潜力；继而深入研究基础技术并呈现其整体框架；随后详细探讨生成式AI驱动的人体数字孪生的实现路径，涵盖生成式AI赋能的数据采集、通信、数据管理、数字建模及数据分析；此外，我们讨论了生成式AI驱动的人体数字孪生可变革的典型物联网医疗应用，即个性化健康监测与诊断、个性化处方及个性化康复；最后，通过展望未来研究方向对本文进行总结。