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Abstract Wearable strain sensors for movement tracking are a promising paradigm to improve clinical care for patients with neurological or musculoskeletal conditions, with further applicability to athletic wear, virtual reality, and next‐generation game controllers. Clothing‐like wearable strain sensors can support these use cases, as the fabrics used for clothing are generally lightweight and breathable, and interface with the skin in a manner that is mechanically and thermally familiar. Herein, a fabric capacitive strain sensor is presented and integrated into everyday clothing to measure human motions. The sensor is made of thin layers of breathable fabrics and exhibits high strains (>90%), excellent cyclic stability (>5000 cycles), and high water vapor transmission rates (≈50 g/h m²), the latter of which allows for sweat evaporation, an essential parameter of comfort. The sensor's functionality is verified under conditions similar to those experienced on the surface of the human body (35°C and % relative humidity) and after washing with fabric detergent. In addition, the fabric sensor shows stable capacitance at excitation frequencies up to 1 MHz, facilitating its low‐cost implementation in the Arduino environment. Finally, as a proof of concept, multiple fabric sensors are seamlessly integrated with commercial activewear to collect movement data. With the prioritization of breathability (air permeability and water vapor transmission), the fabric sensor design presented herein paves the way for future comfortable, unobtrusive, and discrete sensory clothing. 

Soft robot deformations are typically estimated using strain sensors to infer change from a nominal shape while taking a robot‐specific mechanical model into account. This approach performs poorly during buckling and when material properties change with time, and is untenable for shape‐changing robots that don't have a well‐defined resting (unactuated) shape. Herein, these limitations are overcome using stretchable shape sensing (S3) sheets that fuse orientation measurements to estimate 3D surface contours without making assumptions about the underlying robot geometry or material properties. The S3 sheets can estimate the shape of target objects to an accuracy of ≈3 mm for an 80 mm long sheet. The authors show the S3 sheets estimating their shape while being deformed in 3D space and also attached to the surface of a silicone three‐chamber pneumatic bladder, highlighting the potential for shape‐sensing sheets to be applied, removed, and reapplied to soft robots for shape estimation. Finally, the S3 sheets detecting their own stretch up to 30% strain is demonstrated. The approach introduced herein provides a generalized method for measuring the shape of objects without making strong assumptions about the objects, thus achieving a modular, mechanics model‐free approach to proprioception for wearable electronics and soft robotics. 

Abstract Stretchable electronics have potential in wide‐reaching applications including wearables, personal health monitoring, and soft robotics. Many recent advances in stretchable electronics leverage liquid metals, particularly eutectic gallium‐indium (EGaIn). A variety of EGaIn electromechanical behaviors have been reported, ranging from bulk conductor responses to effectively strain‐insensitive responses. However, numerous measurement techniques have been used throughout the literature, making it difficult to directly compare the various proposed formulations. Here, the electromechanical responses of EGaIn found in the literature is reviewed and pure EGaIn is investigated using three electrical resistance measurement techniques: four point probe, two point probe, and Wheatstone bridge. The results indicate substantial differences in measured electromechanical behavior between the three methods, which can largely be accounted for by correcting for a fixed offset corresponding to the resistances of various parts of the measurement circuits. Yet, even accounting for several of these sources of experimental error, the average relative change in resistance of EGaIn is found to be lower than that predicted by the commonly used bulk conductor assumption, referred to as Pouillet's law. Building upon recent theories proposed in the literature, possible explanations for the discrepancies are discussed. Finally, suggestions are provided on experimental design to enable reproducible and interpretable research. 

Abstract Recent work has demonstrated the potential of actuators consisting of bulk elastomers with phase‐changing inclusions for generating high forces and large volumetric expansions. Simultaneously, granular assemblies have been shown to enable tunable properties via different packings, dynamic moduli via jamming, and compatibility with various printing methods via suspension in carrier fluids. Herein, granular actuators are introduced, which represent a new class of soft actuators made of discrete grains. The soft grains consist of a hyperelastic shell and multiple solvent cores. Upon heating, the encapsulated solvent cores undergo liquid‐to‐gas phase change, inducing rapid and strong volumetric expansion of the hyperelastic shell up to 700%. The grains can be used independently for micro‐actuation, or in granular agglomerates for meso‐ and macroscale actuation, demonstrating the scalability of the granular actuators. Furthermore, the active grains can be suspended in a carrier resin or solvent to enable printable soft actuators via established granular material processing techniques. By combining the advantages of phase‐change soft actuation and granularity, this work presents the opportunity to realize soft actuators with tunable bulk properties, compatibility with self‐assembly techniques, and on‐demand reconfigurability.