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ABSTRACT Wearable textile‐based enzymatic biosensors provide a promising engineering platform for non‐invasive and continuous monitoring of physiological biomarkers; however, their practical performance is often constrained by coupled transport and reaction phenomena under realistic operating conditions. In sweat lactate biosensors, limited oxygen availability and local pH variations within thin, quasi‐stagnant sweat films can significantly distort sensitivity, linearity, and detection limits, yet these effects are rarely addressed through predictive engineering analysis. In this work, a one‐dimensional multiphysics model is developed to investigate the coupled diffusion, enzymatic reaction kinetics, acid–base equilibria, and electrochemical transduction governing a textile‐printed lactate biosensor. The system comprises a graphite–polyurethane electrode modified with reduced graphene oxide and Prussian blue, combined with lactate oxidase immobilized in a chitosan hydrogel. The model incorporates dual‐substrate Michaelis–Menten kinetics alongside realistic sweat buffering and oxygen transport constraints. Simulation results demonstrate pronounced local acidification at the enzyme–electrode interface, with pH drops of up to 1.6 units under weak buffering, leading to more than 50% reduction in enzymatic activity. Furthermore, rapid oxygen depletion within the enzyme layer drives the sensor into an oxygen‐limited regime at physiologically relevant lactate concentrations, resulting in nonlinear response behavior and degraded analytical reliability. Sensitivity analysis identifies buffer capacity, maximum enzymatic rate, and oxygen affinity as the dominant engineering parameters controlling sensor performance. The proposed framework provides quantitative design guidelines to improve robustness, linearity, and operational reliability of wearable enzymatic biosensors.
Saleh et al. (Mon,) studied this question.