Search Results (138)

Continuous plantar-pressure monitoring is important for objective gait analysis and early detection of abnormal loading; however, many existing solutions remain laboratory-bound (force plates and instrumented walkways) or rely on costly in-shoe multilayer sensor arrays. Here, we developed and optimized a fully screen-printed pressure-sensing insole based on carbon–polymer nanocomposite layers, with an emphasis on manufacturability and process control to bridge the gap between proof-of-concept force-sensitive resistor (FSR)-based insoles and scalable printed-electronics manufacturing workflows. Composite pastes containing carbon fillers (graphene nanoplatelets, carbon black, and graphite) were formulated to improve sensor repeatability and sensitivity. Sensors were characterized under compression loads from 100 N to 1300 N, showing a sensitivity of 10.5 ± 2.8 Ω per 100 N and a sheet-to-sheet coefficient of variation of 22.1% in resistance response. The effects of paste composition, screen mesh density, electrode layout, and lamination on sensitivity and repeatability were systematically evaluated. In addition, correlation analysis of resistance values from integrated quality-control meanders proved useful for monitoring screen-printing process stability. The final insole integrates printed carbon sensing pads and contacts, a dielectric spacer, and an adhesive layer in a thin, flexible format suitable for integration with wearable electronics. In practical static-load tests, repeated manual placement of weights yielded coefficients of variation as low as 4% at 500 g and a detection limit of ~0.1 N, comparable to a very light finger touch. These results demonstrate that low-cost screen-printed electronics can provide robust pressure sensing for wearable plantar-pressure monitoring. Full article

Low-Temperature Co-Fired Ceramic (LTCC)-based mechanical sensors are inherently limited by the thickness and rigidity of multilayer ceramic stacks, which restrict miniaturization and mechanical compliance. To overcome these constraints, this work presents a hybrid LTCC/Kapton^® platform enabling high-sensitivity mechanical sensing through mechanically tunable RF passive components. The proposed approach integrates a flexible polyimide membrane, bonded onto an LTCC substrate at low temperatures using selectively electroplated indium pillars that simultaneously define the air gap and provide mechanical fixation. Inductance tuning is achieved via metal-shielding proximity effects, whereas capacitance tuning relies on force-controlled air-gap modulation in a metal–insulator–metal configuration. The fabrication process ensures precise gap control, high compliance, and structural robustness without requiring deformable ceramic membranes. Experimental characterization, including three-dimensional surface profiling and impedance measurements, demonstrates a 48% inductance tuning range with a sensitivity of 0.715 nH/mN and a 36% capacitance tuning range with a sensitivity of 47.3 fF/mN at 1 MHz. The proposed hybrid platform provides a compact and scalable solution for high-sensitivity sensors and mechanically reconfigurable RF components suitable for harsh-environment and adaptive electronics applications. Full article

Flexible wearable pressure sensors still face the challenges of complex structure and high manufacturing costs. In this article, we present a simple method for preparing a highly sensitive, flexible wearable pressure sensor based on candle soot and porous PDMS foam. Meanwhile, to enhance the sensor’s robustness and practicality, a fully enclosed packaging design based on PDMS film was developed. The resulting sensor demonstrates excellent sensitivity, attributed to its porous structure, rough surface, and the unique properties of candle soot. Furthermore, the developed sensor can accurately detect movements in various parts of the human body and measure the force applied during finger pressing. This innovative porous PDMS/candle soot pressure sensor shows great potential for applications in wearable electronics. Full article

Solid rocket motors (SRMs) play a pivotal role in space exploration owing to their reliability and high thrust-to-weight ratios. SRM propellant health monitoring is in critical demand owing to the complex operational scenarios throughout the entire life cycle of SRMs. To achieve in situ detection of three-dimensional stress, this study introduces a novel flexible three-dimensional stress sensor (FSS). First, a liquid metal pressure-sensing element with a variable cross-section was designed and numerically modeled. The performance of the FSS under different loading conditions was analyzed using finite element modeling. The sensing element prototype was fabricated using mold casting and liquid metal injection methods. The fabricated sensing-element prototype with an area ratio of 1:5 exhibited a sensitivity coefficient of 1.5%/kPa at a pressure of 300 kPa, a maximum hysteresis error of 3.98%, and a stability error of 0.17%. Finally, the FSS was developed by integrating multiple pressure-sensing elements and encapsulating the force-concentrating layers. The fabricated FSS prototype was characterized using simulated propellant experiments. Via comparison with the simulation results, the FSS was found to detect multiaxial stress differences when embedded within a propellant. Full article

An alternative conductive ink based on carbon nanotubes (CNTs) was developed using a platinum-catalyzed silicone elastomer and isopropyl alcohol (IPA). The inclusion of IPA in the conductive CNT ink facilitated the optimization of its mechanical strength, electrical conductivity, and viscosity. Compared to conventional silicone rubber-based conductive polymers that often solidify in a few hours at room temperature or with heating, this liquid composite of CNT particles and IPA exhibited a prolonged duration of up to several months in a hermetic environment, maintaining chemical stability even with the elastomer and its curing agent. The gradual evaporation of IPA initiates a well-known cross-linking process, leading to stretchability and electrical conductivity derived from the silicone elastomer and CNT particles, respectively. The relationship between the mechanical strength and electrical conductivity of the hardened conductive CNT ink was studied, which helped determine the optimized concentration of CNT particles in the conductive CNT ink. Subsequently, a piezoresistive sensor was designed, fabricated, and evaluated. The conductive CNT ink-based piezoresistive sensor showed high sensitivity and good repeatability with respect to a wide range of external forces. The effect of the concentration of CNT particles on the viscosity of the conductive CNT ink was also investigated, providing a better understanding of the entanglement of CNT particles within the silicone elastomer. A coating test using the conductive CNT ink with a paper cutting machine demonstrated its potential for adaptation to various printing techniques, including screen printing. The proposed conductive CNT ink, characterized by a simple chemical composition, facile fabrication process, use of non-toxic elements, high electrical conductivity, and stretchability, combined with an extended duration, has the potential to be applied for multiple purposes, such as various types of flexible and wearable electronics. Full article

The expansion force generated by lithium-ion batteries during charge–discharge cycles is a key indicator of their structural safety and health. Recently, flexible pressure-sensing technologies have emerged as promising solutions for in situ swelling monitoring, owing to their high flexibility, sensitivity and integration capability. This review provides a systematic summary of progress in this field. Firstly, we discuss the mechanisms of battery swelling and the principles of conventional measurement methods. It then compares their accuracy, dynamic response and environmental adaptability. Subsequently, the main flexible pressure-sensing mechanisms are categorized, including piezoresistive, capacitive, piezoelectric and triboelectric types, and their material designs, structural configurations and sensing behaviors are discussed. Building on this, we examine integration strategies for flexible pressure sensors in battery systems. It covers surface-mounted and embedded approaches at the cell level, as well as array-based and distributed schemes at the module level. A comparative analysis highlights the differences in installation constraints and monitoring capabilities between these approaches. Additionally, this section also summarizes the characteristics of swelling signals and recent advances in data processing techniques, including AI-assisted feature extraction, fault detection and health state correlation. Despite their promise, challenges such as long-term material stability and signal interference remain. Future research is expected to focus on high-performance sensing materials, multimodal sensing fusion and intelligent data processing, with the aim of further advancing the integration of flexible sensing technologies into battery management systems and enhancing early warning and safety protection capabilities. Full article

This study presents the design and implementation of a surface plasmon resonance (SPR) sensor in the Kretschmann configuration, employing a gold film deposited on a flexible polydimethylsiloxane (PDMS) substrate as the SPR chip. The refractive-index sensitivity of the SPR sensor was evaluated with sodium chloride solutions of varying concentrations. Optimizing for both sensitivity and detection accuracy, the incident angle was fixed at 13°. The sensor exhibited a sensitivity of 3385.5 nm/RIU. Remarkably, the sensitivity variation was merely 1% after subjecting the sensor chip to 50 bending cycles in both forward and reverse directions. The sensor’s efficacy was further validated through the detection of alcohol content in three different Chinese Baijiu samples, yielding a maximum relative error of 4.04% and a minimum error of 0.17%. Additionally, the sensor was utilized to study the adsorption behavior of glutathione (GSH) on the gold film under varying pH conditions. The findings revealed optimal immediate adsorption at pH = 12, attributed to the complete deprotonation of mercapto groups, facilitating the formation of Au-S bonds with gold atoms. The best film-forming effect was observed at pH = 7, where the interplay of attractive and repulsive forces among different molecular groups led to the gradual extension of the molecular chain, resulting in a thicker molecular film. Full article

With the increasing number of patients with Parkinson’s disease, the detection of Parkinson’s disease is crucial for the early intervention and treatment of this condition. The motor characteristics of Parkinson’s disease primarily include typical motor features. Flexible pressure sensor arrays, due to their unique mechanical properties and biocompatibility, have shown great potential for capturing movement characteristics. This research aims to develop a deep learning model based on foot pressure data for the detection of Parkinson’s disease. By collecting the pressure data of patients during walking and analyzing the distribution of foot pressure, the model can capture the unique biomechanical characteristics of Parkinson’s disease patients. To address the core challenges of spatial irregularity and data disorder in footprint data, we propose an innovative approach that leverages the Transformer-based attention mechanism and tensor fusion technique to enable accurate identification of Parkinson’s disease. This attention mechanism has inherent permutation invariance, which is highly suitable for the feature learning of footprint data. The tensor fusion technique can effectively integrate the foot features at different levels. A large-scale dataset of foot pressure data was used for training and validation. The experimental results show that the model achieves a high accuracy of 87.03% and good stability in Parkinson’s disease detection, enabling effective differentiation between patients and healthy individuals. On the one hand, our work is critical for analyzing pressure data and fusion features from large-area flexible force-sensitive sensors, which enables the accurate identification of foot data. On the other hand, it greatly facilitates gait analysis, gait evaluation, and the diagnosis of Parkinson’s disease. Full article

Despite the digital era and the emergence of simplified production paradigms enabled by digital twin technology, traditional manufacturing processes like lathe machining are invaluable because of their ability to meet various and multiple needs reliably and flexibly. To combine these processes into smart monitoring and control systems, including tool wear detection and fault diagnosis, precise multi-axis force measurement is necessary. Single-axis sensors are insufficient to measure the entire dynamics of cutting interactions. A new idea based on strain gauge technology for a self-decoupled three-axis force sensor is proposed in this paper, which aims to measure cutting forces and vibration in a lathe operation. During the cutting process, the sensor is designed to independently recognize the onset of forces at three orthogonal axes to enhance real-time process monitoring capabilities. The Timoshenko beam theory is used to design the mechanical structure, where sensitivity could be improved with minimal crosstalk. Finite element analysis (FEA) simulations were conducted to evaluate the sensor’s performance, stress distribution, modal assessments, and interference error. The interference error of 0.31 percent indicated by the results of the simulation is extremely low, indicating a successful decoupling of the force components. These encouraging simulation results indicate that there is a high possibility of applying the proposed sensor design to intelligent manufacturing systems. It presents an initial point of departure into the embodiment of sophisticated monitoring platforms for conventional machining processes, eliminating the discontinuity between old and new smart manufacturing systems. Full article

Flexible pressure sensors are essential for wearable electronics, human–machine interfaces, and soft robotics. However, conventional Polydimethylsiloxane (PDMS)-based sensors often suffer from limited conductivity, poor filler dispersion, and low structural integration with textile substrates. In this work, we present a robotic drop-coating approach for fabricating graphite–copper nanoparticle (G-CuNP)/PDMS composite pressure sensors with textile-integrated electrodes. By precisely controlling droplet deposition, a three-layer sandwiched structure was realized that ensures uniformity and scalability while avoiding the drawbacks of conventional full-line coating. The effects of filler loading and graphite nanoparticle (GNP) and copper nanoparticle (CuNP) ratios were systematically investigated, and the optimized sensor was obtained at 40 wt% total fillers with a graphite content of 55 wt%. The fabricated device exhibited high sensitivity in the low-pressure region, stable performance in the medium- and high-pressure ranges, and an exponential saturation fitting with R² = 0.998. The average hysteresis was 7.42%, with excellent cyclic stability over 1000 loading cycles. Furthermore, a hand-shaped sensor matrix composed of five distributed sensing units successfully distinguished grasping behaviors of lightweight and heavyweight objects, demonstrating multipoint force mapping capability. This study highlights the advantages of robotic drop-coating for scalable fabrication and provides a promising pathway toward low-cost, reliable, and wearable soft pressure sensors. Full article

Children with intoeing gait are at increased risk of tripping and consequent injury, reduced mobility, and psychological issues. Quantification of tripping is needed outside the gait lab during daily life for improved clinical assessment and treatment evaluation and to enrich the database for artificial intelligence (AI) learning. This paper presents the development of a low-cost, wearable tripping monitor to log a child’s Tripping Hazard Events (THEs) and steps taken during two weeks of everyday activity. A combination of sensors results in a high probability of THE detection, even during rapid gait, while guarding against false positives and minimizing power and therefore monitor size. A THE is logged when the feet come closer than a predefined threshold during the intoeing foot swing phase. Foot proximity is determined by a Radio Frequency Identification (RFID) reader in “sniffer” mode on the intoeing foot and a target of passive Near-Field Communication (NFC) tags on the contralateral foot. A Force Sensitive Resistor (FSR) in the intoeing shoe sets a time window for sniffing during gait and enables step counting. Data are stored in 15 min epochs. Laboratory testing and an IRB-approved human participant study validated system performance and identified the need for improved mechanical robustness, prompting a redesign of the monitor. A custom Python (version 3.10.13)-based Graphical User Interface (GUI) lets clinicians initiate recording sessions and view time records of THEs and steps. The monitor’s flexible design supports broader applications to real-world activity detection. Full article

Intrinsically stretchable polymer ionic conductors (PICs) hold significant application prospects in fields such as flexible sensors, energy storage devices, and wearable electronic devices, serving as promising solutions to prevent mechanical failure in flexible electronics. However, the development of PICs is hindered by an inherent trade-off between mechanical robust and electrical properties. Cellulose, renowned for its high mechanical strength, tunable chemical groups, abundant resources, excellent biocompatibility, and remarkable recyclability and biodegradability, offers a powerful strategy to decouple and enhance mechanical and electrical properties. This review presents recent advances in cellulose-based polymer ionic conductors (CPICs), which exhibit exceptional design versatility for flexible electrodes and strain sensors. We systematically discuss optimization strategies to improve their mechanical properties, electrical conductivity, and environmental stability while analyzing the key factors such as sensitivity, gauge factor, strain range, response time, and cyclic stability, where strain sensing refers to a technique that converts tiny deformations (i.e., strain) of materials or structures under external forces into measurable physical signals (e.g., electrical signals) for real-time monitoring of their deformation degree or stress state. Full article

Flexible pressure sensors have shown promise applications in scenarios such as robotic tactile sensing due to their excellent sensitivity and linearity. However, the realization of flexible pressure sensors with both static and dynamic response capabilities still face significant challenges due to the properties of the sensing materials themselves. In this study, we propose a flexible pressure sensor that integrates piezoelectric and ionic capacitance mechanisms for full-domain response detection of dynamic and static forces: a “sandwich” sensing structure is constructed by printing a mixture of multi-walled carbon nanotubes (MWCNTs) onto the surface of the upper and lower electrodes, and sandwiching a polyvinylidene fluoride (PVDF) thin film between the electrodes. The device exhibits a sensitivity of 0.13 kPa⁻¹ in the pressure range of 0–150 kPa. The sensor has a rapid dynamic response (response time 19 ms/12 ms) with a sensitivity of 0.49 mV kPa⁻¹ based on the piezoelectric mechanism and a linearity of 0.9981 based on the ionic capacitance mechanism. The device maintains good response stability under the ball impact test, further validating its potential application in static/dynamic composite force monitoring scenarios. Full article

Tire deformation monitoring is a critical requirement for improving vehicle safety, performance, and intelligent transportation systems. However, most existing flexible strain sensors either lack directional sensitivity or have not been validated in real-world driving environments, limiting their practical application in smart tires. In this work, we report the fabrication of a flexible piezoresistive strain sensor based on a porous laser-induced graphene (LIG) network embedded in an Ecoflex elastomer matrix, with integrated directional force recognition. The LIG–Ecoflex sensor exhibits a high gauge factor of 9.7, fast response and recovery times, and stable performance over 10,000 cycles. More importantly, the anisotropic structure of the LIG enables accurate multi-directional stress recognition when combined with a convolutional neural network (CNN), achieving an overall classification accuracy exceeding 98%. To further validate real-world applicability, the sensor was mounted inside passenger car tires and tested under different loads and speeds. The results demonstrate reliable monitoring of tire deformation with clear correlations to load and velocity, confirming robustness under dynamic driving conditions. This study provides a new pathway for the integration of direction-aware, high-performance strain sensors into intelligent tire systems, with broader potential for wearable electronics, vehicle health monitoring, and next-generation Internet of Vehicles applications. Full article

Wearable pressure sensors have emerged as vital tools in personalized monitoring, promising transformative advances in patient care and diagnostics. Nevertheless, conventional devices frequently suffer from limited sensitivity, inadequate flexibility, and concerns regarding biocompatibility. Herein, we introduce silk fibroin, a naturally occurring protein extracted from silkworm cocoons, as a promising material platform for next-generation wearable sensors. Owing to its remarkable biocompatibility, mechanical robustness, and structural tunability, silk fibroin serves as an ideal substrate for constructing capacitive pressure sensors tailored to medical applications. We engineered silk-derived capacitive architecture and evaluated its performance in real-time human motion and physiological signal detection. The resulting sensor exhibits a high sensitivity of 18.68 kPa⁻¹ over a broad operational range of 0 to 2.4 kPa, enabling accurate tracking of subtle pressures associated with pulse, respiration, and joint articulation. Under extreme loading conditions, our silk fibroin sensor demonstrated superior stability and accuracy compared to a commercial resistive counterpart (FlexiForce™ A401). These findings establish silk fibroin as a versatile, practical candidate for wearable pressure sensing and pave the way for advanced biocompatible devices in healthcare monitoring. Full article