机器学习辅助的可穿戴SERS-微流体系统用于快速检测出汗生物标志物和兴奋剂
Yanjiao Zhang1, Yanxian Guo1, Wen Wang1
1Dongguan Key Laboratory of Medical Electronics and Medical Imaging Equipment, The First Dongguan Affiliated Hospital, School of Biomedical Engineering, Guangdong Medical University, Dongguan, 523808, Guangdong, China.
Analytical and bioanalytical chemistry
|February 11, 2026
概括
一个新的可穿戴设备使用基于纸张的细分圆形微流体表面增强拉曼散射 (SCMP-SERS) 实时分析汗水. 这项技术使运动员的非侵入性监测成为可能.
科学领域:
- 生物医学工程 生物医学工程
- 分析化学 分析化学
- 材料科学 材料科学 材料科学
背景情况:
- 汗水分析提供了一种非侵入性的方法,用于监测运动员在运动期间的生理和代谢状态.
- 现有的汗水分析方法往往缺乏实时能力或需要复杂的样本处理.
- 汗水的化学成分为运动员的健康和表现提供了宝贵的见解.
研究的目的:
- 开发一种可穿戴设备,在体力活动期间实时进行非侵入性汗水分析.
- 创建一个能够对关键的汗水生物标志物进行定量分析的传感器.
- 探索反兴奋剂监测和个性化体育生理监测的潜力.
主要方法:
- 开发一个基于纸的细分圆形微流体表面增强拉曼散射 (SCMP-SERS) 装置.
- 集成基于黄金@碳点的等离子纸,以提高SERS性能 (增强系数高达3.6 × 10^9).
- 整合一个调节流量的微流体网络,用于控制的汗水收集和定量分析,再加上机器学习来识别刺激剂.
主要成果:
- 该SCMP-SERS设备成功地进行了实时汗水分析,识别了尿素,尿酸和乳酸等生物标志物.
- 多通道设计允许在运动期间连续采集汗液样本和纵向SERS量化.
- 机器学习的整合使得识别人工汗水中的兴奋剂的准确率超过97.9%.
结论:
- 开发的可穿戴SCMP-SERS设备为运动员生理状态的非侵入性实时监测提供了一个有前途的平台.
- 这项技术具有实时反兴奋剂监测和个性化的体育生理学应用的巨大潜力.
- 该设备在分析汗液生物标志物和检测非法物质方面表现出高灵敏度和准确性.
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