This work proposes, for the first time, a novel assembly-free electrode design for micro hemispherical resonator gyroscopes ($\mu$-HRGs), along with an integrated process for the simultaneous fabrication of both the resonator and electrodes. The resonator and electrodes are co-fabricated in a single high-temperature molding process of two layers of fused silica, with the electrode-resonator gap precisely defined by the thickness of a pre-deposited metal layer prior to molding process. A temporary electrode interconnection structure is designed to mechanically connect the resonator and electrodes during fabrication, maintaining their relative alignment. After metallization of both the resonator and electrodes, the electrode interconnection structure is selectively removed by laser cutting to electrically isolate the resonator from the electrodes. The fabricated device achieves a total capacitance of 16.06 pF across 16 electrodes, providing a large drive and sense capacitance while eliminating the need for complex assembly processes.
Autonomous microsystems are important for downhole monitoring to enhance the safety and efficiency of oil and gas production. We propose and computationally validate a previously unreported method for localizing autonomous microsystems in downhole environments, based on the time difference of arrival of low-frequency acoustic signals. This method eliminates the need for clock synchronization between the downhole microsystem and surface acoustic sources, and removes the requirement for specialized acoustic components by leveraging existing pressure sensors to detect low-frequency acoustic signals. This work shows that below $80 \text{Hz}, 60 \mathrm{m}$ localization resolution can be achieved at 1.8 km depth.
In this work, we investigate how the selection of PDMS encapsulant, Sylgard 160 and Sylgard 184, affects the transmit and receive performance of immersion coupled PVD PZT PMUTs under the influence of DC bias. First, the benefit of having PDMS encapsulant has been demonstrated through acoustic characterization. Experiments were performed under immersion to determine the TRX frequency responses of the DUTs to show a 998% to 1085% improvement in TRX signal levels with DC bias as compared to the performance without bias for both types of PDMS, respectively. Second, a performance comparison of the encapsulation polymers was performed. Sylgard 160 encapsulated devices displayed 1.61 times more signal strength compared to Sylgard 184 encapsulated devices at their respective peak frequencies.
Ultrasonic imaging is widely used in medical diagnostics and non-destructive testing but remains limited by the trade-off between resolution and imaging depth. This work presents the electromechanical characterization of dualelectrode circular piezoelectric micromachined ultrasonic transducers (PMUTs) for multifrequency operation to address this challenge. Three top electrode configurations: single electrode, dual concentric rings, and disk-ring were designed, fabricated and characterized for mode-selective excitation. Finite element analysis (FEA) guides electrode design by evaluating mode shapes and strain distributions. Devices are fabricated using the PiezoMUMPs process with identical membrane dimensions and materials for fair comparison. Impedance analysis and laser doppler vibrometry (LDV) measurements show strong agreement with simulations. Dual top electrode configuration enables real-time switching between resonant modes, favoring the fundamental mode with dualelectrode excitation and higher-order mode with outer-electrode actuation. The concentric ring configuration demonstrates the strongest overall performance, highlighting the importance of electrode configuration for tunable frequency PMUTs in nextgeneration ultrasound systems.
Porous electrodes are used in multiple resistive, capacitive and electrochemical sensors where the respective porosity and pore morphology play an important role in improving sensing performance. In this work we develop porous polyurethane (PU) foams dip-coated with poly (3, 4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) and show that electrochemical impedance spectroscopy (EIS) coupled with equivalent circuit modeling enables determination of pore diameter. The pores of PU/PEDOT:PSS electrodes are modeled as circular cylindrical channels of uniform diameter and of semiinfinite length and their average diameter is found dependent on dip-coating cycles decreasing from 211 to 156 µm, The modeled data is further benchmarked with mercury porosimetry and conductivity measurements. The ability to non-invasively extract pore dimensions in three-dimensional electrode structures opens new and more affordable avenues for characterizing and improving porous-based sensors performance.
Real-time monitoring of neurotransmitters such as serotonin (5-HT) and dopamine (DA) is critical for understanding brain function and diagnosing neurological disorders. However, conventional neural probes suffer from low sensitivity, rigid structures that damage brain tissue, and limited single-analyte detection. Here, we report a flexible electrochemical fiber sensor for sensitive and simultaneous detection of 5-HT and DA. The sensor is constructed from an expanded carbon nanotube fiber (CNTF) with well-exposed individual CNTs and catalytically active tube ends, offering enhanced electrochemical performance. Integrated with both working and counter fibers, it achieves high sensitivity $(150.1 \mu \mathrm{A} / \mu \mathrm{M}$ for $5-\text{HT}, 70.8 \mu \mathrm{A} / \mu \mathrm{M}$ for DA) and low detection limits (0.025 and $0.1 \mu \mathrm{M}$, respectively) in vitro. For in vivo validation, the sensor allowed real-time monitoring of dopamine dynamics in the rat brain and clearly tracked the DA increasement after L-Dopa administration. This fiber sensor offers a promising implantable device for real-time neurochemical analysis and can be extended to multiplex detection of neurotransmitters.
Magnetic localization is widely used in applications like capsule robotics, where accurate calibration of magnetic sensor arrays is crucial. Traditional methods are time-consuming, requiring many known magnet poses, while existing rotational techniques are inefficient and demand specialized tools. To address these limitations, this paper proposes a fast calibration method based on a novel universal joint-based calibration tool. By reducing the number of optimization parameters from six to two, the method enables rapid calibration of magnetic sensor arrays. For a $4 \times 4$ sensor array, the average calibration time is under 40 seconds. Experimental results show an average position error of 1.96 mm and an average orientation error of 2.79°, demonstrating the effectiveness of the proposed method.
This paper presents a resource-efficient, multi-resolution sliding Occupancy Grid Map (OGM) framework for resource-constrained Micro Aerial Vehicles (MAVs) equipped with RGB-D sensors, addressing the critical trade-off between mapping fidelity and resource consumption. At its core, the framework integrates a sliding map mechanism with a multi-resolution hierarchical structure, enabling dynamic and adaptive adjustment of local region resolution based on perceptual requirements. We further introduce a hybrid update strategy that combines coarse-grained raycasting with a novel adaptive projection check to achieve accurate and efficient map updates. Extensive evaluations on public datasets and flight tests in real-world scenarios demonstrate that our framework substantially reduces memory consumption compared to state-of-the-art methods, while delivering real-time computational performance with update times as low as 11.89 ms.
Our work aims to demonstrate a multi-sensor integration system for wearable health monitoring using a shirt embedded with a thermocouple for temperature sensing and a force sensing resistor (FSR) for acquiring raw voltage measurements to extract respiratory signals via digital signal processing techniques. These sensors continuously capture physiological and biomechanical data, enabling monitoring of body temperature and recovery of respiratory signals and their time-frequency representations via post-processing using continuous wavelet transform method. To improve signal quality and reduce noise, a moving average filter is applied to ensure stable and reliable body temperature. Signal processing enables the early detection of abnormalities such as fever, physical impact, or poor posture. The proposed wearable platform has strong potential for low-cost, real-time physiological monitoring in both clinical and everyday settings. As health monitoring continues to position multisensor data fusion as a critical advancement in healthcare technology.
Surface electromyography (EMG) is perhaps the most widely used control strategy for advanced upper limb prostheses, enabling users to actuate their devices by activating their residual muscles. However, these systems are highly sensitive to electrode shift or changes in contact with the residual limb caused by variations in limb position or grasped loads which can degrade signal quality and reduce control reliability. To address these limitations, researchers have explored combining EMG with force myography (FMG), a complementary sensing modality that captures volumetric changes in the limb. While this multimodal approach has demonstrated improved accuracy, existing EMG+FMG systems are often confined to laboratory setups or involve bulky sensor designs that are impractical for prosthesis integration. Thus, there remains a need for compact, multimodal sensors that retain the form factor of commercially available EMG electrodes while enhancing control robustness. This work addresses this issue by introducing an EMG+FMG sensor that is in the form factor of conventional EMG sensors used for advanced upper limb prosthesis control. Here, we present the design metrics, electrical and mechanical properties of this sensor, and its effectiveness during gesture recognition to demonstrate its potential for upper limb prosthesis integration.
Diabetic foot ulcers (DFUs) are a serious complication of diabetes, often leading to amputations, high mortality rates, and significant healthcare burdens. This study introduces a novel wearable smart insole designed to improve DFU management by enhancing blood circulation and monitoring microvascular health through advanced sensing technologies. The smart insole integrates seven dry-form electrical stimulation electrodes, photoplethysmography (PPG) sensors for blood perfusion monitoring, and capacitive pressure sensors to maintain optimal sensor-to-skin contact during use. A custom-designed stimulation circuit with a voltage-controlled current source and H-bridge configuration ensures stable biphasic charge output across all seven electrodes by dynamically compensating for variations in skin impedance. In a study involving 10 volunteers, the insole significantly increased local blood perfusion by an average of 335%, demonstrating the crucial role of sensor integration in monitoring and improving circulation. These results indicate that the smart insole is capable of promoting local blood flow, an important factor in the healing process of DFUs. This research underscores the importance of wearable sensor technologies in delivering personalized, at-home solutions for managing diabetic complications, offering a promising pathway for developing advanced, non-invasive treatments for individuals at risk of DFUs.
This work presents a novel, reusable, wearable electrochemical sensor for continuous monitoring of hydration through sodium ($\text{Na}^{+}$) and potassium ($\mathrm{K}^{+}$) ion detection in sweat. The sensor was fabricated using a direct-ink-write extrusion printing system, employing a precision dispenser to deposit conductive electrode materials onto flexible substrates with an interfacial layer serving as the ion-to-electron transduction medium. The device architecture integrates silver (Ag) ink for working and counter electrodes, and silver/silver chloride $(\text{A g} / \text{A g C l})$ ink for the reference electrode. Functionalized electrodes enabled selective $\text{Na}^{+}$ and $\mathrm{K}^{+}$ detection. A flexible microfluidic layer was incorporated to regulate sweat flow across the sensing interface, ensuring consistent analyte delivery and supporting continuous operation. The wearable system was electrochemically characterized using cyclic voltammetry in aqueous solutions of potassium ferricyanide $\left(\mathrm{K}_{3} \text{Fe}(\text{CN})_{6}\right)$, potassium ferrocyanide $\left(\mathrm{K}_{4} \text{Fe}(\text{CN})_{6}\right)$, and sodium chloride $(\text{NaCl})$ solution acting as artificial sweat at different concentrations. The platform demonstrated consistent performance and repeatability, highlighting its potential as a low-cost, scalable solution for electrolyte sensing in wearable health monitoring applications.
Non-invasive muscle activity and fatigue monitoring is typically conducted using surface electromyography (EMG). While EMG is widespread, it is prone to electromagnetic interference. Alternatives such as mechanomyography (MMG) have lacked suitable piezoelectric sensors for wearable integration. We present an MMG approach using flexible, 3D-printed ferroelectrets that capture lateral muscle vibrations of the musculus biceps brachii contraction. During the experimental investigation, seven participants performed isometric holds with incremental loads as well as sustained fatigue tests. Both EMG and MMG demonstrate increasing amplitudes across load and time, indicating rising muscle activation and signs of fatigue, respectively. MMG's mean power frequency exhibits a load-induced shift toward higher frequencies, outperforming EMG as an indicator with little to no shift. Our findings demonstrate that EMG is the preferred metric for quantifying gross activation, whereas MMG provides an early spectral marker of fast-twitch fiber recruitment. The results confirm that ferroelectret-based MMG is a viable, non-invasive alternative or complement to EMG for muscle activity and fatigue assessment. The customizable sensors enable seamless integration into wearable systems for applications in rehabilitation, prosthetics, and human-machine interaction.
The paper presents a methodology for calibrating the spatial separation between accelerometer proof masses in a strapdown inertial navigation system (INS) with an arbitrarily oriented accelerometer triad. Unlike conventional calibration techniques that require alignment of accelerometer sensitivity axes with the turntable rotation axis, the proposed approach allows for arbitrary known misalignment. The method relies on a sequence of periodic oscillations of the INS around three orthogonal body-frame axes. By analyzing the induced velocity errors, we derive a parametric model that relates the proof mass separation to the observed velocity drift. The paper provides a description of the calibration procedure and a performance evaluation based on numerical simulations, demonstrating estimated accuracy within 1 mm.
This study presents a novel microfluidic sensor integrating cobalt-specific ion-imprinted polymer (Co-IIP) thin films for the selective optical detection of $\text{Co}^{2+}$ ions in battery recycling streams. The sensor leverages a hybrid material design, combining a metal-organic framework (UiO-66-(OH)2) with ion imprinting to enhance both binding capacity and selectivity. The Co-IIP films, prepared via UV polymerization of a MOF-assisted pre-polymer mixture containing cobalt nitrate and spiropyran dye, were patterned within a four-layer microfluidic device fabricated using pressure-sensitive adhesives and PET substrates. Upon $\text{Co}^{2+}$ binding, spiropyran undergoes a fluorescence-enhancing structural change, enabling real-time optical readout. The sensor exhibited a concentration-dependent fluorescence response with a detection limit of ∼40 mg/L and demonstrated high selectivity over $\text{Ni}^{2+}$ and $\text{Al}^{3+}$. This platform provides a miniaturized, rapid, and scalable alternative to conventional analytical techniques for on-site monitoring of critical metals, supporting sustainable battery recycling and circular economy applications.
Reliable monitoring of gas-releasing reactions is essential for emerging pressure-driven actuation and soft robotic systems. However, real-time sensing is required to analyze the gas release trends and to consistently monitor the reaction kinetics. This work presents a compact pressure-sensing approach to investigate the oxygen release kinetics from the decomposition of anthracene-endoperoxide (ANT-EPO) molecules in an aqueous environment. A sealed setup with a pressure sensor was used to capture the gradual pressure increase resulting from oxygen evolution at room temperature. To extract meaningful kinetic information, a multi-step signal processing pipeline was applied, including baseline offset correction, Savitzky-Golay (SG) smoothing to reduce highfrequency noise, and discrete wavelet transform (DWT) filtering to isolate the reaction-induced pressure trend from the drift. Temperature effects were taken into consideration to account for ambient effects on pressure fluctuation. The processed denoised pressure-time profile revealed distinct kinetic phases and was fitted using both first-order and logistic models. The resulting pressure profile exhibited a sigmoidal form that was described more accurately by a logistic model ($\mathbf{R}^{2}=0.967$, RMSE $=0.19 \text{kPa}$, AIC $=-2.91 \mathrm{e}+06$) than by a first-order exponential ($R^{2}=0.929$). The proposed approach provides a foundation for characterizing slow gas-releasing reactions and supports the development of chemical actuation platforms that rely on controlled gas generation.
This study presents a comprehensive vibrometric characterization of piezoelectric Micromachined Ultrasonic Transducers (pMUTs). Initially, Fast Fourier Transform (FFT) analysis was employed to identify the resonance frequencies of the pMUTs. Subsequently, signals at these resonance frequencies were utilized to measure the displacement and the Q-factor. The pMUTs shared a uniform design but varied in diameter, resulting in resonance frequencies ranging from 200 to 600 kHz. Additionally, a comparative analysis was conducted between two materials: PZT (Lead Zirconate Titanate) and ScAIN30% (Scandium Aluminum Nitride with 30% Scandium), both deposited via Physical Vapor Deposition (PV D). The key findings reveal that while both materials exhibit similar displacement trends, PZT consistently demonstrates displacement values approximately twice as high as those of ScAIN30%. This study provides valuable insights into the performance of pMUTs with varying resonance frequencies and materials, contributing to the advancement of ultrasonic transducer technology.
To optimize CMOS odor sensors for high-density olfactory sensing, it is essential to evaluate the electrical characteristics of odor-sensitive membranes under realistic device conditions. In this study, we designed and fabricated a test structure that emulates the cross-sectional architecture of a CMOS odor sensor pixel. The device supports precise four-terminal impedance measurements and accommodates multiple electrode spacings to assess geometry-dependent effects. Using a conductive polymer membrane, we extracted the resistance $(R_{\text{total}})$ and capacitance $(C_{\text{mem}})$ between the sensing and bias electrodes. The results showed that $R_{\text{total}}$ increased and $C_{\text{mem}}$ decreased with greater electrode spacing. Under NH3 exposure, both parameters exhibited reversible responses with consistent relative changes across different spacings. These findings demonstrate the utility of the test structure as a platform for membrane characterization and provide practical insights for the miniaturization and integration of CMOS-based odor sensor arrays.
To enhance odor selectivity for electronic nose (E-nose) applications, a voltage modulation odor sensing approach based on polymer-based thin-film transistors (TFTs) is proposed. The sensor array was fabricated using eight non-conductive functional polymers (PAS, PC, PMMA, PS, PVA, PVB, PVCA, and SAA) as channel materials, and their responses to five representative odorants were measured under gate voltage sweeping conditions. The voltage-dependent response profiles were visualized using radar plots, and odor discrimination performance was quantitatively evaluated via normalized mean squared error (MSE) analysis. PAS and PVB exhibited average MSE values of 1.711 and 0.918 among the individual polymers. Notably, the combination of PAS and PVB resulted in a significantly higher MSE of 2.168, exceeding the value of 1.3954 observed for the full eight-polymer array and thus demonstrating superior odor selectivity. These results indicate that the synergistic effect of complementary polymer properties and gate bias modulation enables high-dimensional odor discrimination with reduced sensing elements. The gate bias control modulation can effectively simplify sensor architecture while maintaining high odor discrimination capability.
Amorphous, 30 nm layers of Nb2O5or Ta2O5 on 55 nm SiO2 are compared as gate stacks on ISFETs for pH sensing at 60 °C in solution, to see if Nb2O5 can compete with Ta2O5. The high temperature lowers the high threshold voltage caused by trapped charge with experimental layers. The pH is measured from 9 to 6 for ten ISFETs simultaneously over five cycles for use in hot springs and for DNA amplification. Both Group 5 element oxides exhibit a near-Nernstian response of approximately 66 mV/pH at this temperature and pH range. Individual ISFETs are then selected and measured from pH 12 down to near pH 0 at the same temperature for monitoring pH in hydrothermal vents, hot springs, and acid mine drainage, where near-Nernstian behavior is also observed for both oxides.
