Smart healthcare is a framework that utilizes technologies such as wearable devices, the Internet of Medical Things (IoMT), sophisticated machine learning algorithms, and wireless communication technology to seamlessly access health records, link individuals, resources, and organizations, and then effectively handle and react to health environment demands intelligently. One of the main ingredients of smart healthcare is medical sensors or IoMT. Due to the complex nature of diseases, in many cases, there is a need for multimodal medical signals for their diagnoses. While using multimodal signals, the most important issue is how to fuse them – an area of burgeoning interest within the research community. This paper presents a comprehensive survey of multimodal medical signals fusion schemes that have been proposed for smart healthcare applications. Research works included in major repositories, such as IEEE Xplore, Science Direct, Springer Link, and ACM digital library have been surveyed to address several related research questions. Focus is placed on recent developments, thus only works published between 2014-2020 are considered. Finally, key research challenges and possible future directions are also provided.

智慧医疗是一种利用可穿戴设备、医疗物联网（IoMT）、复杂的机器学习算法和无线通信技术等技术无缝访问健康记录，链接个人、资源和组织，然后有效处理和智能地响应健康环境需求。智能医疗保健的主要成分之一是医疗传感器或 IoMT。由于疾病的复杂性，在很多情况下，需要多模式医学信号来进行诊断。在使用多模信号时，最重要的问题是如何融合它们——这是研究界内一个新兴的兴趣领域。本文对为智能医疗保健应用提出的多模态医疗信号融合方案进行了全面调查。包括在主要知识库中的研究工作，如 IEEE Xplore、Science Direct、Springer Link 和 ACM 数字图书馆已经过调查，以解决几个相关的研究问题。重点放在最近的发展上，因此只考虑 2014-2020 年间发表的作品。最后，还提供了关键的研究挑战和未来可能的方向。