Xu Changhao, Song Yu, Sempionatto Juliane R, Solomon Samuel A, Yu You, Nyein Hnin Y Y, Tay Roland Yingjie, Li Jiahong, Heng Wenzheng, Min Jihong, Lao Alison, Hsiai Tzung K, Sumner Jennifer A, Gao Wei
Andrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, USA.
These authors contributed equally to this work.
Nat Electron. 2024 Feb;7(2):168-179. doi: 10.1038/s41928-023-01116-6. Epub 2024 Jan 19.
Approaches to quantify stress responses typically rely on subjective surveys and questionnaires. Wearable sensors can potentially be used to continuously monitor stress-relevant biomarkers. However, the biological stress response is spread across the nervous, endocrine, and immune systems, and the capabilities of current sensors are not sufficient for condition-specific stress response evaluation. Here we report an electronic skin for stress response assessment that non-invasively monitors three vital signs (pulse waveform, galvanic skin response and skin temperature) and six molecular biomarkers in human sweat (glucose, lactate, uric acid, sodium ions, potassium ions and ammonium). We develop a general approach to prepare electrochemical sensors that relies on analogous composite materials for stabilizing and conserving sensor interfaces. The resulting sensors offer long-term sweat biomarker analysis of over 100 hours with high stability. We show that the electronic skin can provide continuous multimodal physicochemical monitoring over a 24-hour period and during different daily activities. With the help of a machine learning pipeline, we also show that the platform can differentiate three stressors with an accuracy of 98.0%, and quantify psychological stress responses with a confidence level of 98.7%.
量化应激反应的方法通常依赖于主观调查和问卷。可穿戴传感器有可能用于持续监测与应激相关的生物标志物。然而，生物应激反应分布于神经、内分泌和免疫系统，目前传感器的能力不足以进行特定状况下的应激反应评估。在此，我们报告一种用于应激反应评估的电子皮肤，它能无创监测人体汗液中的三项生命体征（脉搏波形、皮肤电反应和皮肤温度）以及六种分子生物标志物（葡萄糖、乳酸、尿酸、钠离子、钾离子和铵）。我们开发了一种制备电化学传感器的通用方法，该方法依赖类似的复合材料来稳定和保护传感器界面。所得传感器能够对汗液生物标志物进行超过100小时的长期分析，且稳定性高。我们表明，这种电子皮肤能够在24小时内以及不同日常活动期间提供连续的多模态物理化学监测。借助机器学习流程，我们还表明该平台能够以98.0%的准确率区分三种应激源，并以98.7%的置信水平量化心理应激反应。
