ABSTRACT With the cross‐integration of flexible electronics and artificial intelligence technologies, high‐sensitivity wearable sensors have shown great potential in fields such as medical rehabilitation, human‐computer interaction, and sports science. To meet the dual requirements of high sensitivity and flexibility for wearable applications, this study proposes a novel sandwich‐structured P(VDF‐TrFE)/BTO‐OH/P(VDF‐TrFE) piezoelectric sensor (SP‐sensor) using a fused deposition modeling (FDM) process. This structure effectively combines the high piezoelectricity of BTO nanoparticles with the excellent flexibility of the P(VDF‐TrFE) polymer, overcoming the limitations of traditional single‐layer piezoelectric sensors. Experimental results demonstrate that the piezoelectric response voltage and current of the SP‐sensor are enhanced by 51.1% and 546%, respectively, compared with those of single‐layer P(VDF‐TrFE) films. With improved piezoelectric performance, the SP‐sensor achieves approximately 50% higher sensitivity than the traditional designs. It also exhibits quick response and recovery capabilities, with a response time of 8.1 ms and a recovery time of 64 ms. Additionally, it exhibits excellent fatigue resistance, with no noticeable voltage decay observed after 18,000 cycles of testing. An intelligent wrist motion recognition system, integrating a deep learning algorithm (CNN model), was developed based on this SP‐sensor, enabling real‐time classification of three types of wrist movement patterns with an identification accuracy of 97.85%. This study, through the innovation in material structure and the integration of AI algorithms, paves the way for the application of next‐generation wearable devices in human‐machine interaction and medical diagnosis.

ABSTRACT The heart's electrical function is known to adapt to physiological demands, but the mechanisms by which gravitational force may modulate conduction remain unexplored. Understanding this could reshape interpretations of cardiac electrical behavior in altered gravity, such as during long‐term spaceflight. Microgravity induces changes in cardiac morphology, fluid distribution, and autonomic regulation, linked to rhythm disturbances including QT prolongation and sudden cardiac death. Current explanations remain largely indirect, attributing electrical changes to haemodynamic or autonomic factors. Conventional ECG lacks the spatial resolution to determine whether gravity directly affects propagation. Here, we investigate whether gravitational loading directly alters cardiac conduction by examining posture‐driven shifts in gravitational vectors in a controlled ground‐based model. We developed a high‐density electrode array to perform localized body surface potential mapping, enabling the extraction of conduction‐sensitive propagation features. Using machine learning classification, we demonstrate that postural changes can be reliably detected based solely on these features, something not achievable with standard ECG metrics. These results suggest that cardiac conduction is not merely responding to systemic physiological feedback but is sensitive to changes in gravitational orientation through its effects on the spatial configuration of conductive myocardial tissue. This suggests a previously unrecognized mechanism by which gravity can directly influence cardiac electrophysiology. Our findings highlight a limitation in current cardiac monitoring systems, particularly in extreme environments such as space. By identifying gravity‐sensitive features of cardiac conduction, this work opens a path to new diagnostic tools and a deeper physiological understanding of the heart's adaptation to altered gravitational states.

ABSTRACT Miniaturized grippers are essential for manipulating objects in confined spaces, such as minimally invasive surgery or inspection tasks in narrow spaces. Conventional miniaturized designs struggle to balance structural simplicity with complex motion, as well as low energy consumption with sufficient energy release. Bistable structures—especially bistable shells—offer a promising solution by enabling rapid, energy‐efficient self‐shape transitions. However, bistable shell–driven grippers face two major challenges: (1) their shape transition typically depends on external actuation systems that increase system complexity and hinder miniaturization, and (2) the fabrication of bistable shells at millimeter‐scale remains technically challenging, limiting their integration into compact devices. This work proposes a miniaturized bistable gripper confined within a 15‐mm‐diameter cylindrical envelope. It is based on a plastically formed prestressed shell whose two stable states can be mechanically switched. Compared with existing bistable grippers, often larger than 50 mm, the proposed design significantly reduces size while maintaining reliable bistable performance. Moreover, the miniaturized fabrication process of bistable shells was investigated to identify geometric and forming conditions that ensure robust bistability under millimeter‐scale constraints. The resulting gripper offers a structurally simple, energy‐efficient solution with reliable performance in constrained spaces, showing strong potential for micromanipulation, surgical robotics, and confined‐environment tasks.

ABSTRACT Liquid crystal elastomers (LCEs) are a promising class of active materials for soft robotic actuation, capable of generating complex 3D deformations. Existing approaches to complex‐form actuation with LCEs have largely focused on either global stimulation to produce a single preprogrammed 3D shape or local stimulation using light‐controlled or multi‐circuitry methods to achieve multiple complex forms. However, these approaches have notable limitations: single‐shape actuation restricts operational capability; light‐actuated systems are hindered by occlusion and require non‐compliant, bulky components, compromising compactness, compliance, and mobility; and embedded circuitry designs increase fabrication complexity while limiting achievable deformation to the number of embedded circuits. Here, we present an electrically controlled actuation method, termed dynamic current routing, which employs a continuous, homogeneous conductive LCE surface to generate a large number of complex 3D deformations using only a few input electrodes. The system is fully compliant, compact, scalable, generalisable, and field‐programmable. The actuator's capabilities are demonstrated through multi‐gait, multi‐directional locomotion, highlighting the potential of multi‐complex deformation for soft robotics and wearables applications.

ABSTRACT Electrochemical biosensors enable the accurate and timely detection of clinical biomarkers, improving healthcare and precision medicine. MXene nanosheets, a class of 2D transition metal carbides, nitrides, and carbonitrides, are promising materials for developing next‐generation electrochemical biosensors due to their unique physicochemical properties, including high electrical conductivity, a large specific surface area, and an abundance of surface terminal groups, rendering them hydrophilic and well‐suited for the surface immobilization of biorecognition elements and their transduction of into analytical signals. This review highlights the recent progress in MXene‐based electrochemical biosensors for clinical biomarker detection, focusing on their biofunctionalization approaches (including covalent and non‐covalent approaches, as well as hybrid materials) and electrochemical biosensing strategies based on biomarker type (proteins, nucleic acids, metabolites, cells, and extracellular vesicles). We discuss factors affecting their sensitivity, selectivity, and dynamic range, highlighting how material design can be leveraged to optimize biosensor functions. Moreover, we provide a forward‐thinking perspective on the challenges that hinder the translation of MXene‐based biosensors into clinical practice. We emphasize the importance of developing stable and bio‐orthogonal biofunctionalization strategies, as well as multiplexed biosensing strategies, to achieve meaningful applications of MXenes in the clinical practice based on the ultrasensitive detection of clinically relevant biomarkers.

ABSTRACT Wireless temperature sensing with passive LC resonators can be significantly enhanced by integrating dielectric materials whose permittivity varies with temperature. In this work, we present a set of 3D‐printed porous ceramic lattices engineered from a multicomponent metal‐oxide ink that serve as tunable dielectrics for temperature‐responsive sensing. The ink, composed of Mn, Ni, Co, Cu, and Zn oxides, is processed through ball milling, 3D printing, debinding, and sintering to produce porous structures with porosities of 54%, 39%, and 24%. Structural and dielectric characterizations confirm that permittivity increases with temperature and decreases with porosity. When positioned on a planar LC sensor and interrogated using a vector network analyzer (VNA), the samples exhibit distinct resonant frequency shifts over the range of 25°C–110°C. Higher dielectric samples show lower resonant frequencies and stronger temperature sensitivity, with Δf/ΔT slopes that are both steep and sample‐specific. Electromagnetic simulations using HFSS closely match experimental S21 data, supporting the observed sensing trends. This work demonstrates a versatile strategy for customizing wireless temperature sensors by tuning the porosity and composition of printed ceramic dielectrics.

ABSTRACT Transducers underpin modern sensing, actuation, and modulation by converting physical signals into electrical or optical representations. Despite rapid advances across materials, fabrication, and device architectures, individual transduction mechanisms remain constrained by intrinsic trade‐offs among bandwidth, sensitivity, speed, energy consumption, and integrability. This review examines transducer technologies across mechanical, acoustic, electromagnetic, and optical domains, and shows that performance evolution is not only increasingly governed by the discovery of new mechanisms, but also by the system‐level coordination of established ones. By organizing representative platforms according to physical scale, operating frequency, and accessible degrees of freedom, we reveal how distinct mechanisms occupy complementary performance envelopes across Hertz‐to‐THz regimes. We highlight how heterogeneous integration and multiphysics co‐design enable these envelopes to be traversed through coordinated architectures that combine flexible interfaces, electromechanical systems, metasurfaces, and photonic circuits. This perspective reframes transducers from isolated interfaces into programmable system nodes that jointly support sensing, modulation, and information processing. The resulting framework provides a foundation for designing reconfigurable and scalable transducer systems for sustainable applications, precision imaging, adaptive communication, edge intelligence, and emerging quantum technologies.

ABSTRACT Recent advancements in bioinspired vision systems have expanded the capabilities of wearable sensors and electronics, enabling a closer integration between human perception and digital health interfaces. This review explores how visual augmentation technologies, inspired by compound eyes, curved retinas, and light‐adaptive mechanisms, are being translated into flexible, skin‐conformal, and mechanically adaptive healthcare platforms. These bioinspired systems not only enhance the field of view (FoV), depth perception, and dynamic adaptation, but also enable interactive and intelligent functionality when embedded in wearable form factors, such as soft sensors, optical skins, and exoskeletal frameworks. We further analyze the underlying materials, structural architectures, and sensory modalities that enable such integration and highlight their applications in artificial intelligence (AI) assisted rehabilitation, remote health monitoring, and human‐machine collaborative systems. Despite remarkable progress, challenges remain in ensuring long‐term biocompatibility, real‐time data processing, and system‐level stability. This review concludes by identifying emerging opportunities to advance the convergence of bioinspired optics, neuromorphic sensing, and AI‐based digital healthcare toward next‐generation human‐machine augmentation.

ABSTRACT Two‐terminal optoelectronic synapses have garnered great attention in neuromorphic computing due to their advantages in structural simplicity and energy efficiency. However, the device's operational flexibility is fundamentally limited by its spectral and electrical characteristics, which fail to tune photoresponses with wavelength selectivity and voltage modulation. Here, a MoS 2 /Au nanoparticle two‐terminal optoelectronic synapse is presented that simultaneously achieves wavelength selectivity and voltage‐modulated memory control. Adjusting the morphology of Au nanoparticles enables selective maximum photoresponses across the green and red wavelength regions, and voltage modulation induces switching between short‐term and long‐term memory states, thereby enhancing functional versatility. Based on this tunable photoresponse of the synapse, wavelength‐selective image denoising and recognition tasks are demonstrated, achieving a maximum classification accuracy of 98.03% at 520 nm across the visible wavelength range. A wavelength‐selective and voltage‐modulated task for road condition classification is also implemented, incorporating an artificial neural network to track color‐coded vehicles and classify their movement trajectories with precise directional recognition (96.67% accuracy). This work demonstrates a highly tunable optoelectronic synapse that achieves concurrent wavelength selectivity and voltage modulation in a single device, enabling neuromorphic computing and providing a practical strategy for developing highly efficient, multifunctional neuromorphic architectures.

ABSTRACT WS 2 ‐based field‐effect transistors (FETs), photodetectors, and other devices utilizing the back‐gated (BG) architecture are prone to spontaneous oxidation and adsorption of ambient molecules, degrading their performance and reliability. Also, a significantly high contact resistance (R C ) is another bottleneck limiting their performance. This work addresses these issues by using a dual‐layer passivation technique, which enables n‐type doping, charge impurity screening, and trap suppression in WS 2 , boosting the performance and reliability of WS 2 ‐based FETs and photodetectors. Here, the e‐beam‐evaporated Al 2 O 3 is used as the first passivation layer, which, using the density functional theory (DFT) and Raman and photoluminescence (PL) spectra, is found to induce significant n‐type doping in WS 2 . This doping improves the field‐effect mobility (µ FE ) and R C of WS 2 FETs by shielding the electrons in the FET's channel from coulomb impurities and narrowing the Schottky barrier width, respectively. Further, a second passivation layer of a more uniform atomic layer deposition (ALD)‐deposited Al 2 O 3 is used, which assists in providing effective passivation. Using this technique, the µ FE and R C of WS 2 FETs improved by ∼108% and ∼800%, respectively, enhancing their I ON and I ON /I OFF by ∼700% and ∼2 orders, respectively. Moreover, the photocurrent and responsivity of the WS 2 ‐based photodetector improved by around 178 times.