基于AgNW/MXene的机器学习驱动可穿戴汗液传感器用于无创sers心血管疾病检测

IF 5.5 2区 材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY
Zhaoxian Chen, Yao Liu, Wenrou Yu, Shihong Liu* and Yingzhou Huang*, 
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引用次数: 0

摘要

传统的心血管疾病诊断依赖于侵入性检测方法,这可能会引起患者的焦虑或不适。无创诊断技术(如可穿戴传感器)可减少这些顾虑,具有显著优势。表面增强拉曼光谱(SERS)是一种超灵敏技术,非常适合疾病诊断,尤其是与机器学习(ML)算法相结合时。在本研究中,我们将 AgNW/MXene 羟基复合膜作为 SERS 底物,用于检测汗液中的胆固醇。MXene 的高比表面积增强了对目标分子的吸附,从而提高了 SERS 信号的灵敏度。在 10-8 M 的浓度下成功检测到了胆固醇,证明了该方法在 50 个拉伸释放周期中的稳健性。采用随机森林(RF)模型对健康人和心血管病人的汗液样本进行分类,准确率达到 83.5%。与传统的侵入性方法相比,我们的方法提供了一种非侵入性、高灵敏度和耐用性的替代方法,而且还具有易于集成到可穿戴诊断设备中的优势。这些可穿戴汗液传感器的高灵敏度和耐用性突显了它们在推进无创心血管疾病检测方面的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Machine Learning-Driven Wearable Sweat Sensors with AgNW/MXene for Non-Invasive SERS-Based Cardiovascular Disease Detection

Machine Learning-Driven Wearable Sweat Sensors with AgNW/MXene for Non-Invasive SERS-Based Cardiovascular Disease Detection

Traditionally, cardiovascular disease diagnosis has relied on invasive testing methods, which may cause anxiety or discomfort in patients. Noninvasive diagnostic technologies, such as wearable sensors, offer significant advantages by reducing these concerns. Surface-enhanced Raman spectroscopy (SERS) is an ultrasensitive technique well-suited for disease diagnosis, particularly when combined with machine learning (ML) algorithms. In this study, we introduce AgNW/MXene hydroxyl composite membranes as SERS substrates for cholesterol detection in sweat. The high specific surface area of MXene enhances the adsorption of target molecules, thereby improving SERS signal sensitivity. Cholesterol was successfully detected at a concentration of 10–8 M, demonstrating the robustness of the method over 50 stretch-release cycles. A random forest (RF) model was employed to classify sweat samples from healthy individuals and cardiovascular patients, achieving an accuracy of 83.5%. Compared to traditional invasive methods, our approach provides a noninvasive, highly sensitive, and durable alternative with the added advantage of easy integration into wearable diagnostic devices. The high sensitivity and durability of these wearable sweat sensors highlights their potential for advancing noninvasive cardiovascular disease detection.

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来源期刊
CiteScore
8.30
自引率
3.40%
发文量
1601
期刊介绍: ACS Applied Nano Materials is an interdisciplinary journal publishing original research covering all aspects of engineering, chemistry, physics and biology relevant to applications of nanomaterials. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important applications of nanomaterials.
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