受生物受体启发的软传感器阵列:推进数字医疗的最新进展

Soft science Pub Date : 2023-08-24 DOI:10.20517/ss.2023.23
F. Arab Hassani
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引用次数: 0

摘要

软传感器技术的最新进展将数字医疗保健推向了改变生活的解决方案。数据的可靠性和鲁棒性可以通过构建传感器阵列来实现,这些传感器阵列可以同时从潜在器官的几个点收集全面的生物参数数据,这是一种受生物受体启发的原理。软光刻和印刷、三维(3D)打印以及编织/编织技术的快速发展促进了阵列格式软传感器的低成本发展。数据采集、处理和可视化技术的进步有助于使用阵列收集有意义的数据,并通过无线通信接口将其呈现给个人设备上的用户。本地或基于云的数据存储有助于从传感器阵列中收集足够的数据,以促进基于历史数据的可靠预测。新兴的能量收集技术导致了可持续地为传感器阵列供电的技术的发展。本文综述了可穿戴和人工器官软传感器阵列的发展基础,包括生物受体激发的传感机制,制造方法,数字数据采集技术,向用户展示结果的方法,电力系统,以及用于治疗或监测的目标疾病/条件。最后,我们总结了与先进数字医疗保健的单模和多模阵列传感器开发相关的挑战,并提出了克服这些挑战的可能解决方案。
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Bioreceptor-inspired soft sensor arrays: recent progress towards advancing digital healthcare
Recent advances in soft sensor technology have pushed digital healthcare toward life-changing solutions. Data reliability and robustness can be realised by building sensor arrays that collect comprehensive biological parameter data from several points on the underlying organs simultaneously, a principle that is inspired by bioreceptors. The rapid growth of soft lithography and printing, three-dimensional (3D) printing, and weaving/knitting technologies has facilitated the low-cost development of soft sensors in the array format. Advances in data acquisition, processing, and visualisation techniques have helped with the collection of meaningful data using arrays and their presentation to users on personal devices through wireless communication interfaces. Local- or cloud-based data storage helps with the collection of adequate data from sensor arrays over time to facilitate reliable prognoses based on historical data. Emerging energy harvesting technologies have led to the development of techniques to power sensor arrays sustainably. This review presents developmental building blocks in wearable and artificial organ-based soft sensor arrays, including bioreceptor-inspired sensing mechanisms, fabrication methods, digital data-acquisition techniques, methods to present the results to users, power systems, and target diseases/conditions for treatment or monitoring. Finally, we summarise the challenges associated with the development of single and multimodal array sensors for advanced digital healthcare and suggest possible solutions to overcome them.
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