School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China.
Biosensors (Basel). 2022 Jul 12;12(7):516. doi: 10.3390/bios12070516.
Wearables developed for human body signal detection receive increasing attention in the current decade. Compared to implantable sensors, wearables are more focused on body motion detection, which can support human-machine interaction (HMI) and biomedical applications. In wearables, electromyography (EMG)-, force myography (FMG)-, and electrical impedance tomography (EIT)-based body information monitoring technologies are broadly presented. In the literature, all of them have been adopted for many similar application scenarios, which easily confuses researchers when they start to explore the area. Hence, in this article, we review the three technologies in detail, from basics including working principles, device architectures, interpretation algorithms, application examples, merits and drawbacks, to state-of-the-art works, challenges remaining to be solved and the outlook of the field. We believe the content in this paper could help readers create a whole image of designing and applying the three technologies in relevant scenarios.
在当前十年中,用于人体信号检测的可穿戴设备受到越来越多的关注。与植入式传感器相比,可穿戴设备更专注于人体运动检测,可支持人机交互(HMI)和生物医学应用。在可穿戴设备中,广泛呈现了基于肌电图(EMG)、力肌电图(FMG)和电阻抗断层成像(EIT)的人体信息监测技术。在文献中,所有这些技术都已被用于许多类似的应用场景,这使得研究人员在开始探索该领域时感到困惑。因此,在本文中,我们详细回顾了这三种技术,从基本原理(包括工作原理、设备架构、解释算法、应用示例、优点和缺点)到最新研究成果、待解决的挑战和该领域的展望。我们相信本文中的内容可以帮助读者在相关场景中设计和应用这三种技术时形成整体形象。