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Abstract Mimicking the human eye’s ability to autonomously adapt to diverse and mixed illumination conditions remains a fundamental challenge in artificial vision systems. Although substantial progress has been made in materials and device engineering, current adaptive vision architectures still depend heavily on complex circuitry or algorithms and are typically restricted to uniform illumination owing to the strong intensity-dependence of photosensitivity. Here, this work presents a highly adaptive TiO₂/PEDOT:PSS photomemristor that leverages the tunable conductivity of PEDOT:PSS together with the optoelectronic response of TiO₂. The photothermal effect dynamically modulates the water absorption/desorption equilibrium in PEDOT:PSS, enabling reversible suppression or enhancement of photosensitivity under bright or dim illumination, respectively. By combining with artificial neural networks (ANNs), the artificial vision system based on TiO₂/PEDOT:PSS photomemristor arrays achieves a high accuracy of 91.3% in image recognition under mixed-light conditions—without the need for complex circuitry or algorithms. This work may establish a new approach for designing autonomous, efficient, and high-performance neuromorphic vision systems to advance the development of autonomous driving and humanoid robots. 

In situ monitoring of sweat glucose during exercise can provide a real-time and continuous assessment of blood glucose dynamics. However, the relatively poor correlation between sweat and blood glucose concentrations during exercise makes it challenging for blood glucose management (BGM) during exercise therapy for diabetes, along with training for athletes and fitness enthusiasts. This work presents a flexible wireless sweat glucose and pH sensing platform integrated with a pH-based correlation model to accurately predict the continuous changes in blood glucose. The pH-based correlation model calibrates enzyme activity changes in glucose oxidase and accounts for the effects of sweat dilution and filtering during paracellular transport of glucose from interstitial fluid and plasma to sweat during exercise. The correlation model has been validated in both healthy individuals and diabetic patients, revealing distinct blood glucose dynamic patterns between the two cohorts. The observed different glucose fluctuations after the intake of various nutritive foods further facilitate the management of diabetes and allow for the identification of hypo-/hyperglycemic risks during training or fitness exercise. The exercise-based device platform combines continuous blood glucose monitoring with diabetes management through effective treatment evaluation and can also provide early prevention for the at-risk population and reduce or even reverse diabetes. 

Abstract The concentration of dopamine (DA) and tyrosine (Tyr) reflects the condition of patients with Parkinson's disease, whereas moderate paracetamol (PA) can help relieve their pain. Therefore, real‐time measurements of these bioanalytes have important clinical implications for patients with Parkinson's disease. However, previous sensors suffer from either limited sensitivity or complex fabrication and integration processes. This work introduces a simple and cost‐effective method to prepare high‐quality, flexible titanium dioxide (TiO₂) thin films with highly reactive (001)‐facets. The as‐fabricated TiO₂film supported by a carbon cloth electrode (i.e., TiO₂–CC) allows excellent electrochemical specificity and sensitivity to DA (1.390 µA µM⁻¹ cm⁻²), Tyr (0.126 µA µM⁻¹ cm⁻²), and PA (0.0841 µA µM⁻¹ cm⁻²). More importantly, accurate DA concentration in varied pH conditions can be obtained by decoupling them within a single differential pulse voltammetry measurement without additional sensing units. The TiO₂–CC electrochemical sensor can be integrated into a smart diaper to detect the trace amount of DA or an integrated skin‐interfaced patch with microfluidic sampling and wireless transmission units for real‐time detection of the sweat Try and PA concentration. The wearable sensor based on TiO₂–CC prepared by facile manufacturing methods holds great potential in the daily health monitoring and care of patients with neurological disorders. 

Abstract General movements (GMs) have been widely used for the early clinical evaluation of infant brain development, allowing immediate evaluation of potential development disorders and timely rehabilitation. The infants’ general movements can be captured digitally, but the lack of quantitative assessment and well‐trained clinical pediatricians presents an obstacle for many years to achieve wider deployment, especially in low‐resource settings. There is a high potential to explore wearable sensors for movement analysis due to outstanding privacy, low cost, and easy‐to‐use features. This work presents a sparse sensor network with soft wireless IMU devices (SWDs) for automatic early evaluation of general movements in infants. The sparse network consisting of only five sensor nodes (SWDs) with robust mechanical properties and excellent biocompatibility continuously and stably captures full‐body motion data. The proof‐of‐the‐concept clinical testing with 23 infants showcases outstanding performance in recognizing neonatal activities, confirming the reliability of the system. Taken together with a tiny machine learning algorithm, the system can automatically identify risky infants based on the GMs, with an accuracy of up to 100% (99.9%). The wearable sparse sensor network with an artificial intelligence‐based algorithm facilitates intelligent evaluation of infant brain development and early diagnosis of development disorders. 

Abstract CO₂electroreduction (CO₂R) operating in acidic media circumvents the problems of carbonate formation and CO₂crossover in neutral/alkaline electrolyzers. Alkali cations have been universally recognized as indispensable components for acidic CO₂R, while they cause the inevitable issue of salt precipitation. It is therefore desirable to realize alkali‐cation‐free CO₂R in pure acid. However, without alkali cations, stabilizing *CO₂intermediates by catalyst itself at the acidic interface poses as a challenge. Herein, we first demonstrate that a carbon nanotube‐supported molecularly dispersed cobalt phthalocyanine (CoPc@CNT) catalyst provides the Co single‐atom active site with energetically localizeddstates to strengthen the adsorbate‐surface interactions, which stabilizes *CO₂intermediates at the acidic interface (pH=1). As a result, we realize CO₂conversion to CO in pure acid with a faradaic efficiency of 60 % at pH=2 in flow cell. Furthermore, CO₂is successfully converted in cation exchanged membrane‐based electrode assembly with a faradaic efficiency of 73 %. For CoPc@CNT, acidic conditions also promote the intrinsic activity of CO₂R compared to alkaline conditions, since the potential‐limiting step, *CO₂to *COOH, is pH‐dependent. This work provides a new understanding for the stabilization of reaction intermediates and facilitates the designs of catalysts and devices for acidic CO₂R. 

Abstract Skin‐interfaced high‐sensitive biosensing systems to detect electrophysiological and biochemical signals have shown great potential in personal health monitoring and disease management. However, the integration of 3D porous nanostructures for improved sensitivity and various functional composites for signal transduction/processing/transmission often relies on different materials and complex fabrication processes, leading to weak interfaces prone to failure upon fatigue or mechanical deformations. The integrated system also needs additional adhesive to strongly conform to the human skin, which can also cause irritation, alignment issues, and motion artifacts. This work introduces a skin‐attachable, reprogrammable, multifunctional, adhesive device patch fabricated by simple and low‐cost laser scribing of an adhesive composite with polyimide powders and amine‐based ethoxylated polyethylenimine dispersed in the silicone elastomer. The obtained laser‐induced graphene in the adhesive composite can be further selectively functionalized with conductive nanomaterials or enzymes for enhanced electrical conductivity or selective sensing of various sweat biomarkers. The possible combination of the sensors for real‐time biofluid analysis and electrophysiological signal monitoring with RF energy harvesting and communication promises a standalone stretchable adhesive device platform based on the same material system and fabrication process.