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 more than 100 h 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%.

量化压力反应的方法通常依赖于主观调查和问卷。可穿戴传感器可用于持续监测与压力相关的生物标志物。然而，生物应激反应遍及神经、内分泌和免疫系统，当前传感器的能力不足以评估特定条件的应激反应。在这里，我们报告了一种用于压力反应评估的电子皮肤，它可以无创地监测人体汗液中的三种生命体征（脉冲波形、皮肤电反应和皮肤温度）和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，该方法依赖于类似的复合材料来稳定和保护传感器接口。由此产生的传感器可提供超过 100 小时的长期汗液生物标志物分析，并且具有高稳定性。我们证明电子皮肤可以在 24 小时内和不同的日常活动中提供连续的多模式理化监测。在机器学习管道的帮助下，我们还表明该平台可以以 98.0% 的准确度区分三种压力源，并以 98.7% 的置信度量化心理压力反应。