模块化组装的智能微针平台用于机器学习驱动的个性化健康监测
Hongyi Sun1,2, Lechen Chen3, Tao Wang4
1School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241, People's Republic of China.
Nano-micro letters
|February 9, 2026
概括
一个新的电子生物传感器补丁 (eMPatch) 使用微针进行最少侵入性,对关键代谢生物标志物的实时监测. 机器学习增强了其预测健康评估能力,以实现个性化的医疗保健.
科学领域:
- 生物医学工程 生物医学工程
- 可穿戴技术可穿戴技术
- 生物感应是一种生物感应.
背景情况:
- 下一代医疗保健需要对各种生物标志物的持续,非侵入性监测,以实现个性化的健康管理.
- 当前数据驱动的分析方法与现实世界的定量健康状况预测相扎.
- 代谢途径和病原体具有固有的复杂性,需要先进的监测解决方案.
研究的目的:
- 开发一种可穿戴的生物传感器贴片,用于实时监测多种代谢生物标志物的最小侵入性监测.
- 将微针技术与灵活的平台集成为可靠的皮肤传感.
- 采用机器学习来使用生物传感器数据进行先进的健康评估和预测.
主要方法:
- 设计和制造了一种基于电子多重微针的生物传感器补丁 (eMPatch).
- eMPatch将模块化微针传感器集成到一个灵活的皮肤接口平台上.
- 在动物模型中进行了体内验证,并使用机器学习算法进行数据分析.
主要成果:
- eMPatch成功地实现了实时,最小侵入性监测葡萄糖,尿酸,胆固醇,,和间歇性液体中的pH值.
- 在体内研究表明,在各种活动中强大的机械稳定性和可靠的连续传感.
- 机器学习集成在区分代谢状态和精确评估方面实现了高精度 (0.996) (R2=0.977).
结论:
- 微针集成生物传感器贴片 (eMPatch) 显示了个性化健康管理的巨大潜力.
- 这个平台提供了一个有前途的方法,用于在现实环境中持续的多生物标志物监测.
- 机器学习增强显著提高了可穿戴生物传感器的诊断和评估能力.
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