Stretchable and biocompatible hydrogel-based strain sensors have been considered as promising candidates for flexible wearable electronics in the light of their properties being similar to those of biological tissues. To date, excellent mechanical performances and high sensitivity are still challenging to satisfy the practical applications. In this work, a flexible strain senor is made of patterned liquid metal (LM) sandwiched by poly(acrylamide-co-acrylic acid)/Zr⁴⁺ (P(AAm-co-AAc)/Zr⁴⁺) hydrogel with a bilayer structure. The carboxyl–Zr⁴⁺ coordination bonds endow the prepared hydrogel substrate with moderate water content, as well as spectacular and adaptable mechanical properties. In addition, LM is doped with silicon oxide particles as a conductive layer to improve the sensitivity of the flexible sensor. The flexible sensor combines sensing performances of high sensitivity (maximum gauge factor = 7.16), an ultralow detection limit (0.1%), and a wide strain sensing range (up to 400%). LM-hydrogel strain sensors demonstrate reliable detection of repeated large strains and small vibrations of human movements. As a proof of concept, the sensor can be utilized to detect finger rehabilitation training in different periods owing to the controllable mechanical response. Furthermore, by introducing machine learning, the device with the sensor detects the writing words quickly and accurately, indicating that human activities have been recognized with proper training, which is an important premise for human–machine interaction.

Piezoelectric sensors with good flexibility and high sensitivity have attracted extensive interest in wearable electronics. Here, we report a novel frequency-response behaviour of piezoelectric voltage of a sensor that is based on a piezoelectric enhanced composite film of P(VDF-TrFE) and BaTiO₃. The piezoelectric voltage enhances with the increase of frequency and becomes stable beyond the critical frequency. Such a demonstrated sensing characteristic of the piezoelectric sensor depends on the inner resistance of the voltmeter, which is determined by whether the loading of stimuli can be completed within the period of piezoelectric voltage measurement in the testing circuit. By utilizing the frequency-response behaviour in different frequency ranges, the flexible piezoelectric device exhibits excellent capabilities to quantitatively detect the magnitude and loading rate of stimuli. As a proof-of-concept demonstration, a flexible pressure sensor is successfully integrated with a bionic bee to monitor the flight status (i.e., strain rate and strain) of the vibrating wings. This work demonstrates that flexible piezoelectric sensors have great prospects for application in the field of bionic flying robots, thus paving the way forward for the development of smart self-sensing flexible electronics.

Wearable sweat sensors are essential for providing insight into human physiological health. The currently developed microfluidic sweat sensors have demonstrated the function of collecting and storing sweat. However, they detect more average concentrations of substances based on time periods, which leads to the fact that in situ real-time measurement for multiple biomarkers remains a grand challenge. Here, we propose a wearable epidermal microfluidic patch with integrated microfluidic pumps and micro-valves for accelerated and continuous collection of the sweat, where the micro-pumps ensure the complete separation of old and new sweat for real-time detection of real concentration of biomarkers in sweat. The biomarker concentration at different time periods is detected by introducing a burst valve, which is used to assist in the analysis of the real-time detection. A quantitative relationship between the minimum burst pressure difference required for sequential collection and the size of the microchannel structure is established to overcome the effects of additional resistance at the gas–liquid interface. Additionally, the sensing modules, including sodium ion, chlorine ion, glucose, and pH level in sweat, are integrated into the patch to realize in situ, real-time detection of multiple biomarkers in the human sweat, decoding the correlation between changes in substance concentrations and physiological conditions. This work provides a unique and simplifying strategy for developing wearable sweat sensors for potential applications in health monitoring and disease diagnostics.

A magnetic shape memory hydrogel incorporating Fe ₃ O ₄ with reversible actuation, adjustable stiffness and shape locking property is developed for inductive heating under an alternating magnetic field and deformation under an actuation magnetic field.

In addition to the common blood and urine, fresh sweat contains a diverse range of physiological indicators that can effectively reflect changes in the body’s state. Wearable sweat sensors are crucial for understanding human physiological health; however, real-time in situ measurement of multiple biomarkers in sweat remains a significant challenge. Here, we propose a wearable microfluidic patch featuring an integrated microfluidic channel and evaporation pump for accelerated and continuous sweat collection, eliminating the need for additional sweat storage cavities that typically impede real-time detection. Capillary forces are harnessed to facilitate the rapid flow of sweat through the detection area, while an evaporation pump based on porous laser-induced graphene enhances sweat evaporation. The synergistic integration of these two components enables an uninterrupted flow of fresh sweat within the patch, ensuring real-time monitoring. The influence of channel size parameters on sweat flow velocity is analyzed, and the optimal width-to-height ratio for achieving the desired flow velocity is determined. By implementing a multi-channel parallel design with chamfering, liquid flow resistance is effectively reduced. Furthermore, the patch integrates sensor modules for sodium ion, chloride ion, glucose, and pH value measurements, ensuring excellent sealing and stability of the assembled system. This work presents a simplified approach to developing wearable sweat sensors that hold the potential for health monitoring and disease diagnosis.