Wearable Electrochemical Sweat Sensors Beyond Snapshots With Long‐Term Stability

Abstract

Wearable sweat electrochemical sensors enable continuous and noninvasive monitoring of electrolytes, metabolites, and stress‐related biomarkers for personalized healthcare. However, the translation of these platforms from proof‐of‐concept prototypes to reliable clinical tools is hindered by a critical bottleneck of long‐term operational stability. In realistic wearable scenarios, complex biofouling, fluctuating microenvironments, and dynamic physical deformations collectively trigger degradation pathways that severely compromise signal fidelity. In this review, we establish a stability‐centered framework to systematically untangle the multi‐dimensional failure mechanisms across four primary sensing modalities, including ion‐selective potentiometric, enzymatic, nanozyme‐based, and affinity‐based sensors. State‐of‐the‐art mitigation strategies are then discussed, encompassing materials engineering, device architecture, and computational calibration. Furthermore, critical challenges and prospects encompassing AI‐driven material discovery, continuous sampling, and edge‐computing‐assisted analytics are introduced, serving as a timely resource to accelerate the translation of wearable electrochemical sensors into reliable platforms for comprehensive health management.