A sensitive double-clamped quartz tuning fork (QTF) pressure sensor with temperature compensation for liquid level sensing at elevated temperatures

Reactive dye-reinforced PVA-based high-strength, highly conductive coloured hydrogel flexible sensors for joint monitoring and pressure sensing

Bamboo cellulose fiber/Aramid nanofiber/MXene porous composite membrane pressure sensor with wide sensing range and long-term stability for motion monitoring and handwriting recognition

A novel bidirectional high overload piezoresistive differential pressure sensor based on topology optimization

High-reliability backside absolute piezoresistive pressure sensors for automotive applications

Quasi-static and transient signal monitoring based on lithium niobate piezoelectric pressure sensor

Enhanced-performance flexible pressure sensors enabled by synergistic effect of hierarchical porous structures for motion sensing and deep learning-assisted speech recognition.

Single-sided capacitive pressure sensor with tunable performance over a wide pressure range

Intelligent soft gripper with independently controlled multi-segment structure and conformally integrated all-nanofiber pressure sensor for achieving multifunctional grasping capability

A novel dynamic temperature compensation method for silicon pressure sensors in marine environments

In low-vision patients, traditional measures often fall short of capturing functional vision improvements. The study aims to assess the reliability and validity of a novel functional low-vision outcome assessment, the Multi-luminance Shape Discrimination Test (MLSDT). This is a prospective, observational study in 25 participants with severe vision loss due toretinitis pigmentosa (RP) with visual acuity worse than or equal to LogMAR 1.6, and in 10 normal vision participants. The MLSDT utilizes three differently shaped objects, randomly positioned on pressure sensors, to enable an automated, quantifiable response in a controlled multi-luminance environment. The assessment accuracy (recognizing the correct object and picking it up) was measured using the MLSDT. Convergent validity of MLSDT was evaluated with measures of visual acuity and visual field, as well as patient-reported outcomes. The 35 study participants (60% male and 40% female) had a mean age of 46.5years old (range: 19-78years), with 24 Hispanic individuals. Estimates of test-retest reliability for MLSDT exceeded 0.50. The correlations between MLSDT test scores and LogMAR visual acuity were strong (> -0.7). For a difference of 0.3 LogMAR between the groups of RP participants, a decrease of ~ 2-level MLSDT score was observed. Moderate to strong correlations were also observed between MLSDT test scores and the measures of visual field and patient-reported outcome measures. Psychometric evaluation demonstrates the reliability and validity of the novel functional vision endpoint, MLSDT. The MLSDT test performance in participants with different visual acuities showed improved object recognition when the luminance level was enhanced.

Ionogels combine the mechanical softness of polymers with the ionic conductivity and nonvolatility of ionic liquids, offering a versatile platform for wearable electronics and sensing applications. In particular, their high deformability and ionic responsiveness make them attractive dielectric materials for capacitive pressure sensors. However, conventional ionogels often exhibit dielectric saturation and nonlinear responses at elevated pressures, limiting their usable operating range. Here, we report ion-pair-tuned ionogels that balance ionic mobility and polarizability to mitigate dielectric saturation and broaden the linear sensing range up to the megapascal level while maintaining high sensitivity. To validate broad-range functionality-from subtle physiological pressures to large mechanical loads-we integrate the ionogels into intraocular pressure sensors and prosthetic interface monitors, representing low- and high-pressure regimes. These demonstrations establish ion-pair tuning as an effective strategy for achieving broad linear sensing performance in wearable pressure sensors.

The Glean® Urodynamics System was developed to enable catheter-free, wireless assessment of lower urinary tract function for use in ambulatory urodynamic testing. This study assesses the performance of the Glean Urodynamics System relative to the Laborie Goby™ conventional urodynamics (UDS) system using a human bladder model. Thirty Glean intravesical pressure sensors and 30 air-charged catheters were compared relative to a reference sensor. Three pressure simulations were conducted in the bench-top human bladder model (stepped, sinusoidal, and ramping) on each test device to evaluate rise and fall times, bandwidth, maximum error (accuracy), and linearity. Data are presented as means and standard deviations and compared using independent sample t-tests. The Glean intravesical pressure sensors showed significantly faster rise time (0.104 seconds) and fall time (0.111 seconds) than the comparator (0.172 and 0.264 seconds, respectively; both, p < 0.001 between groups). The bandwidth of the Glean sensors more closely matched the tested maximum frequency of 5 Hertz (Hz) compared with the comparator (4.978 Hz vs 2.250 Hz; p < 0.001). The maximum error was significantly lower with the Glean sensors than the comparator (6.882 vs 21.549; p < 0.001). Linearity showed that both behaved linearly; however, the Glean sensors performed significantly better (p < 0.001 between groups). Comparative testing demonstrated equivalent or better performance of the Glean Urodynamics System's intravesical pressure sensors relative to a conventional UDS system's air-charged catheters, including greater bandwidth, increased dynamic response, and reduced maximum error. These results support the superior performance of the Glean Urodynamics System for urodynamic monitoring over a conventional catheter-based UDS system.

Humanoid robots and human-machine interaction technologies are essential for perceiving and manipulating millimeter-scale objects with irregular surfaces in extreme environments, such as outer space, radioactive zones, and hazardous sites with explosive ordnance, where human access is restricted. A vision-based perception approach provides spatial and positional information about objects but relying solely on it for robot manipulation poses challenges due to limitations in detectable object size, as well as sensitivity to external factors such as focusing issues, occlusion, and lighting conditions. In contrast, tactile perception offers valuable information about aspects that are difficult to discern visually, including an object's shape, surface characteristics, and the forces involved during contact. This study presents a complementary visual localization and tactile mapping framework that allows robots to effectively perceive small objects with irregular surfaces in visually restricted environments. The proposed method draws inspiration from the sequential vision-tactile sensory processing observed in humans when handling small objects with irregular surfaces. It employs an RGB-Depth camera for visual perception and a soft pressure sensor array, made using inkjet printing, for tactile perception. We demonstrate the feasibility of implementing a sensory substitution to detect the size and location of objects through visual perception, as well as identify object surfaces and reconstruct their three-dimensional profiles using tactile scanning, particularly in environments where visual information is limited. This study provides a technological foundation for enhancing the autonomy and adaptability of humanoid robots in unpredictable and unstructured environments, particularly to support precise robot manipulation in such conditions.

Human pain perception is a representative sensory function that activates self-protection mechanisms. The inability to detect pain can lead to serious injury and permanent damage. To emulate pain sensation, the sensor should be capable of detecting a broad range of pressures, while efficiently filtering out minor or harmless tactile inputs. To address this critical need, we developed a broadband pressure sensor that mimics human nociceptors and can detect both tactile and pain stimuli. This sensor comprises an air gap and ion gel composite for varying the capacitance according to the applied pressure. This can distinguish the small, moderate, and painful touches using hardware-based (air gap) and software-based thresholding. The sensor can set the hardware threshold (0.1 mm gap) as 200 kPa and achieve a wide sensing range up to 3.6 MPa with high sensitivity (11.2 kPa-1) and excellent linearity within the range ∼900 kPa. The sensor integrated into a prosthetic hand exhibited an avoidance feedback response under stimuli exceeding the pain threshold. This iontronic sensor has potential applications in wearable monitoring, prosthetic tactile feedback, and protective systems for collaborative robots, providing a technological basis for safer interaction in individual with pain insensitivity.

The inherent nonlinearity and limited multimodal sensing capabilities of conventional flexible sensors hinder their applications in complex scenarios such as wearable health monitoring and human-machine interaction. Here, a fully solid-state sensor based on MXene/silk fibroin (SF) composite membrane is proposed, which features expanded interlayer spacing and enhanced mechanical strength, achieving a linear and self-powered conversion of both pressure- and light-driven ionic conversion to electrical responses. In force-electric conversion mode, the current and voltage sensitivity of the obtained pressure sensor with solid electrolyte can reach 2.667mA m-2 kPa-1 and 0.083mV kPa-1, respectively. In light-electric conversion mode, the switching ratio of current is as high as 2658.0, and the response time is as fast as 25ms. The dual-mode synergy was successfully applied to wearable physiological monitoring, acoustic wave recognition, image recognition, and information encryption, establishing a new paradigm for next-generation bionic sensing systems.

Tesla valves are passive flow-control devices that enables asymmetry without moving parts. In recent years, they have attracted renewed interest due to their wide range of applications, spanning from biomedical and agricultural systems to thermal and marine engineering. The performance of a 3D-printed double Tesla valve is experimentally investigated using an integrated low-cost Internet of Things (IoT) measurement system. The valve performance is evaluated for inlet volumetric flow rates ranging from 5 to 20 L/min. The results demonstrate a clear asymmetry between forward and reverse flow, with a maximum diodicity of 1.96 observed at the lowest (5–6 L/min) flow rate. The proposed low-cost experimental framework combines additive manufacturing and real-time IoT-based monitoring, offering a reproducible and accessible approach for investigating passive flow-control devices at flow-rate regimes beyond typical microfluidic applications.

Polyvinylidene fluoride (PVDF) is widely used in flexible, self-powered pressure sensors due to its superior piezoelectric properties, although it necessitates the development of a ferroelectric polarized phase for such applications. In recent years, a piezoionic-electronic architecture integrating PVDF with Nafion has emerged, allowing PVDF polarization through mechanical stress alone and thereby streamlining device design and fabrication. To further boost the piezoelectric efficacy of these devices, this work introduces an MXene-based enhancement strategy. Specifically, a trilayered PVDF/Nafion-MXene/PVDF film (referred to as PNMP) was fabricated using hot-pressing, with subsequent mechanical bending to induce self-polarization in the PVDF components. Investigations reveal that the superior piezoelectric properties of the PNMP films originate from the multifunctional role of MXene: aiding Nafion's proton transport while constructing an electron transmission channel, enhancing charge accumulation at the Nafion/PVDF interface, and promoting β-phase formation in PVDF. The fabricated sensor exhibits an extensive pressure-sensing range from 4.7 to 867.0 kPa, a sensitivity of 64.5 mV/kPa, a rapid response of 0.5 ms, an elevated piezoelectric power density of 660 mW/m2, and excellent operational durability of 200,000 strikes. The PNMP film's real-world utility was demonstrated via applications like powering LEDs, kinetic energy harvesting, and tracking human movements, highlighting its potential for wearable technologies, energy harvesting, and precise mass sensing. This study provides insightful guidance for advancing next-generation piezoionic-electronic piezoelectric systems.

Smart textiles capable of reliable pressure sensing are essential for emerging wearable and biomedical applications; however, scalable fabrication routes that combine sensing performance, durability, and biological safety remain limited. This research presents a green engineered MoS 2 -functionalized nonwoven fabric that was developed as a flexible piezoresistive pressure sensor using a citric-acid-assisted exfoliation and coating approach. Few-layer MoS 2 nanosheets were uniformly coated on the fibrous substrate, forming a flexible conductive network without compromising fabric flexibility. The structural and surface studies confirm the successful intercalation of MoS 2 with well-preserved layered structures. The fabricated textile shows a stable and repeatable electromechanical response in the applied pressure range of 600–6,000 Pa, wherein resistance decreases monotonically while voltage output increases as load is exerted. The sensor exhibits good repeatability (±0.05 V), low hysteresis (0.07 V), and a stable signal (response and recovery), and sustained electrical function was obtained over multiple washing cycles, implying practical robustness. Furthermore, antibacterial activity against Escherichia coli and Staphylococcus aureus is demonstrated, and in vitro cytocompatibility tests indicate 79% cell viability at the highest tested concentration. These findings indicate that green engineered MoS 2 -coated nonwoven fabrics represent a promising platform for pressure-responsive smart textiles, enabling their integration into wearable and bio-interfacing applications.

Achieving high electrical output while maintaining reliable performance under humid, skin-contact conditions remains a critical bottleneck for textile-based self-powered sensors. In this work, we develop a Janus nanofiber mat that integrates asymmetric wettability with interfacial polarization modulation to simultaneously regulate moisture transport and enhance triboelectric output. The architecture consists of a hydrophilic PVP/CA layer, a conductive Ag nanowire interlayer, and a hydrophobic F-POSS/P(VDF-TrFE) layer. This multilayer configuration generates simultaneous gradients in pore size and surface energy, forming directional moisture-transport pathways that rapidly dissipate sweat and help stabilize the interfacial triboelectric state. The incorporation of F-POSS enriches polar phases in P(VDF-TrFE) and significantly reduces the surface potential, as revealed by KPFM, thus enhancing tribonegative polarization and improving charge retention capacity. Benefiting from this cooperative interfacial engineering, the Janus device delivers a peak power density of 0.98 W m-2, high pressure sensitivities of 4.28 VkPa-1 and 3.14 mAkPa-1, and maintains significantly improved output retention across 50-100% RH. The textile platform also serves as a soft, skin-conformable pressure sensor capable of discriminating between joint motion and plantar pressure, and directly powers commercial LEDs and capacitors. This study highlights the potential of interfacial polarization engineering within Janus nanofiber systems as a powerful route to achieve breathable and high-output wearable energy harvesters.