Department of Electrical and Computer Engineering, Rice University, Houston, Texas 77005, United States.
Andrew and Peggy Cherng Department of Medical Engineering, California Institute of Technology, Pasadena, California 91125, United States.
ACS Nano. 2024 Sep 10;18(36):24605-24616. doi: 10.1021/acsnano.4c10344. Epub 2024 Aug 26.
Sweat analysis has advanced from diagnosing cystic fibrosis and testing for illicit drugs to noninvasive monitoring of health biomarkers. This article introduces the rapid development of wearable and flexible sweat sensors, highlighting key milestones and various sensing strategies for real-time monitoring of analytes. We discuss challenges such as developing high-performance nanomaterial-based biosensors, ensuring continuous sweat production and sampling, achieving high sweat/blood correlation, and biocompatibility. The potential of machine learning to enhance these sensors for personalized healthcare is presented, enabling real-time tracking and prediction of physiological changes and disease onset. Leveraging advancements in flexible electronics, nanomaterials, biosensing, and data analytics, wearable sweat biosensors promise to revolutionize disease management, prevention, and prediction, promoting healthier lifestyles and transforming medical practices globally.
汗液分析已经从囊性纤维化和非法药物检测发展到了对健康生物标志物的非侵入性监测。本文介绍了可穿戴和灵活汗液传感器的快速发展，重点介绍了实时监测分析物的关键里程碑和各种传感策略。我们讨论了一些挑战，例如开发基于高性能纳米材料的生物传感器、确保持续的汗液产生和采样、实现高汗液/血液相关性和生物相容性。本文还介绍了机器学习在增强这些传感器以实现个性化医疗方面的潜力，从而能够实时跟踪和预测生理变化和疾病发作。利用灵活电子、纳米材料、生物传感和数据分析方面的进展，可穿戴汗液生物传感器有望彻底改变疾病管理、预防和预测方式，促进更健康的生活方式，并在全球范围内改变医疗实践。
