用于健康监测的可穿戴传感器的进展和挑战

摘要(中文译文)

分析工具可能通过实现可及、快速和分散式检测而彻底改变医疗保健。可穿戴（生物）传感器尤其能够通过无创至微创测量提供频繁或持续的患者监测。这种方法产生前所未有的健康相关信息量，从而实现更明智的临床决策和更密切的患者随访。在这篇大型综述文章中，我们汇集了该领域的顶尖研究人员，讨论用于健康监测的可穿戴设备的最新进展。我们首先通过引文网络分析对该领域进行广泛概述。然后，我们综述化学（生物）传感器在生物体液（如汗液、唾液、泪液、组织间液和脑脊液）中的应用，重点介绍每种体液相关的挑战和优势。随后，我们讨论可穿戴设备的构建及其主要形式（如智能隐形眼镜、纺织品、护齿器、手表/腕带和可植入系统）。物理传感器在专门章节中讨论，重点关注心率、血压和体温的评估。柔性电子器件在可穿戴设备中的作用也予以考察，因为这些技术对于提升用户舒适度和传感器可靠性至关重要，而这需要材料科学的进步。此外，我们介绍信号采集和传输的策略，以及体表能量收集和设备自供电的方法。随后讨论人工智能和机器学习的使用，作为增强分析性能和管理可穿戴设备产生的大量数据的手段。最后，审视商业、监管和伦理方面的考量。我们期望这篇综述能够提供健康相关应用中传感和生物传感技术的概述，识别有前景的研究方向，并启发未来的发展。

Abstract

Analytical tools may revolutionize healthcare by enabling accessible, rapid, and decentralized testing. Wearable (bio)sensors, in particular, provide frequent or continuous patient monitoring through non- to minimally invasive measurements. This approach yields unprecedented amounts of health-related information, leading to more informed clinical decision-making and closer patient follow-up. In this mega-review article, we bring together leading researchers in the field to discuss the state of the art in wearable devices for health monitoring. We begin by providing a broad overview of the field through citation network analysis. We then review the application of chemical (bio)sensors in biofluids (e.g., sweat, saliva, tears, interstitial fluid, and cerebrospinal fluid), highlighting the challenges and advantages associated with each. Subsequently, we discuss the construction of wearable devices and their main formats (e.g., smart contact lenses, textiles, mouthguards, watches/wristbands, and implantable systems). Physical sensors are addressed in a dedicated section focusing on the assessment of heart rate, blood pressure, and body temperature. The role of soft electronics in wearable devices is also examined, as these technologies are essential for enhancing user comfort and sensor reliability, which demands advances in materials science. Furthermore, we present strategies for signal acquisition and transmission, as well as approaches for on-body energy harvesting and device self-powering. The use of artificial intelligence and machine learning is then discussed as a means of enhancing analytical performance and managing the large volumes of data generated by wearable devices. Finally, business, regulatory, and ethical considerations are examined. We expect that this review will provide an overview of sensing and biosensing technologies for health-related applications, identify promising research directions, and inspire future developments.

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