Battery-free, wireless microfluidic/electronic system for multiparameter sweat analysis.

Battery-free, soft, skin-mounted wireless sensors enable continuous, full-body spatiotemporal mapping of pressure and temperature on human subjects.

Soft electromechanical sensors have led to a new paradigm of electronic devices for novel motion-based wearable applications in our daily lives. However, the vast amount of random and unidentified signals generated by complex body motions has hindered the precise recognition and practical application of this technology. Recent advancements in artificial-intelligence technology have enabled significant strides in extracting features from massive and intricate data sets, thereby presenting a breakthrough in utilizing wearable sensors for practical applications. Beyond traditional machine-learning techniques for classifying simple gestures, advanced machine-learning algorithms have been developed to handle more complex and nuanced motion-based tasks with restricted training data sets. Machine-learning techniques have improved the ability to perceive, and thus machine-learned wearable soft sensors have enabled accurate and rapid human-gesture recognition, providing real-time feedback to users. This forms a crucial component of future wearable electronics, contributing to a robust human–machine interface. In this review, we provide a comprehensive summary covering materials, structures and machine-learning algorithms for hand-gesture recognition and possible practical applications through machine-learned wearable electromechanical sensors.

This review focuses on the silver nanowires (Ag NWs) based stretchable and flexible energy devices for self-sustainable devices.

Hydrogels have diverse chemical properties and can exhibit reversibly large mechanical deformations in response to external stimuli; these characteristics suggest that hydrogels are promising materials for soft robots. However, reported actuators based on hydrogels generally suffer from slow response speed and/or poor controllability due to intrinsic material limitations and electrode fabrication technologies. Here, we report a hydrogel actuator that operates at low voltages ( 50%, energy density > 7 × 10 ⁵ joules per cubic meter, and power density > 3 × 10 ⁴ watts per cubic meter), surpassing existing hydrogel actuators and other types of electroactive soft actuators. The enhanced performance of our actuator is due to the formation of wrinkled nanomembrane electrodes that exhibit high conductivity and excellent mechanical deformation through capillary-assisted assembly of metal nanoparticles and deswelling-induced wrinkled structures. By applying an electric potential through the wrinkled nanomembrane electrodes that sandwich the hydrogel, we were able to trigger a reversible and substantial electroosmotic water flow inside a hydrogel film, which drove the controlled swelling of the hydrogel. The high energy efficiency and power density of our wrinkled nanomembrane electrode–induced actuator enabled the fabrication of an untethered insect-scale aquabot integrated with an on-board control unit demonstrating maneuverability with fast locomotion speed (1.02 body length per second), which occupies only 2% of the total mass of the robot.

A millimeter-scale multifunctional soft gripper provides mechanical and thermal stimulation as well as biosignal sensing.