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3D 打印的类液电子皮肤用于基于机器学习的多模式健康监测。

3D-printed epifluidic electronic skin for machine learning-powered multimodal health surveillance.

机构信息

Andrew and Peggy Cherng Department of Medical Engineering, California Institute of Technology, Pasadena, CA 91125, USA.

出版信息

Sci Adv. 2023 Sep 15;9(37):eadi6492. doi: 10.1126/sciadv.adi6492. Epub 2023 Sep 13.

Abstract

The amalgamation of wearable technologies with physiochemical sensing capabilities promises to create powerful interpretive and predictive platforms for real-time health surveillance. However, the construction of such multimodal devices is difficult to be implemented wholly by traditional manufacturing techniques for at-home personalized applications. Here, we present a universal semisolid extrusion-based three-dimensional printing technology to fabricate an epifluidic elastic electronic skin (e-skin) with high-performance multimodal physiochemical sensing capabilities. We demonstrate that the e-skin can serve as a sustainable surveillance platform to capture the real-time physiological state of individuals during regular daily activities. We also show that by coupling the information collected from the e-skin with machine learning, we were able to predict an individual's degree of behavior impairments (i.e., reaction time and inhibitory control) after alcohol consumption. The e-skin paves the path for future autonomous manufacturing of customizable wearable systems that will enable widespread utility for regular health monitoring and clinical applications.

摘要

可穿戴技术与物理化学传感能力的融合有望为实时健康监测创建强大的解释和预测平台。然而,对于家庭个性化应用,此类多模态设备的构建很难完全通过传统制造技术来实现。在这里,我们提出了一种通用的半固态挤出式三维打印技术,用于制造具有高性能多模态物理化学传感能力的液流弹性电子皮肤(e-skin)。我们证明,e-skin 可以作为一个可持续监测平台,在日常活动中实时捕捉个体的生理状态。我们还表明,通过将 e-skin 收集的信息与机器学习相结合,我们能够预测个体在饮酒后的行为障碍程度(即反应时间和抑制控制)。e-skin 为未来可定制的可穿戴系统的自主制造铺平了道路,这将为常规健康监测和临床应用提供广泛的实用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67e0/10499321/4faa50d8f05c/sciadv.adi6492-f1.jpg

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