Search Results (59)

Neuromuscular robotic prostheses have emerged as a critical convergence point between biomedical engineering, machine learning, and human–machine interfaces. This work provides a narrative state-of-the-art review regarding recent developments in robotic prosthetic technology, emphasizing sensor integration, actuator architectures, signal acquisition, and algorithmic strategies for intent decoding. Special focus is given to non-invasive biosignal modalities, particularly surface electromyography (sEMG), as well as invasive approaches involving direct neural interfacing. Recent developments in AI-driven signal processing, including deep learning and hybrid models for robust classification and regression of user intent, are also examined. Furthermore, the integration of real-time adaptive control systems with surgical techniques like Targeted Muscle Reinnervation (TMR) is evaluated for its role in enhancing proprioception and functional embodiment. Finally, this review highlights the growing importance of modular, open-source frameworks and additive manufacturing in accelerating prototyping and customization. Progress in this domain will depend on continued interdisciplinary research bridging artificial intelligence, neurophysiology, materials science, and real-time embedded systems to enable the next generation of intelligent prosthetic devices. Full article

Magnetic tunnel junctions (MTJs) are pivotal for spintronic applications such as magneto resistive memory and sensors. Two-dimensional van der Waals heterostructures offer a promising platform for miniaturizing MTJs while enabling the twist-angle engineering of their properties. Here, we investigate the impact of twisting the insulating barrier layer on the performance of a van der Waals MTJ with the structure graphene/1T-VSe₂/h-BN/1T-VSe₂/graphene, where 1T-VSe₂ serves as the ferromagnetic electrodes and the monolayer h-BN acts as the tunnel barrier. Using first-principles calculations based on density functional theory (DFT) combined with the non-equilibrium Green’s function (NEGF) formalism, we systematically calculate the spin-dependent transport properties for 18 distinct rotational alignments of the h-BN layer (0° to 172.4°). Our results reveal that the tunneling magnetoresistance (TMR) ratio exhibits dramatic, rotation-dependent variations, ranging from 2328% to 24,608%. The maximum TMR occurs near 52.4°. An analysis shows that the twist angle modifies the d-orbital electronic states of interfacial V atoms in the 1T-VSe₂ layers and alters the spin polarization at the Fermi level, thereby governing the spin-dependent transmission through the barrier. This demonstrates that rotational manipulation of the h-BN layer provides an effective means to engineer the TMR and performance of van der Waals MTJs. Full article

Measuring weak magnetic fields proposes significant challenges to the sensing capabilities of magnetic field sensors. The magnetic field detection capacity of tunnel magnetoresistance (TMR) sensors is often insufficient for such applications, necessitating targeted optimization strategies to improve their performance in weak-field measurements. Utilizing magnetic flux concentrators (MFCs) offers an effective approach to enhance TMR sensitivity. In this study, the finite element method was employed to analyze the effects of different MFC geometric structures on the uniformity of the magnetic field in the air gap and the magnetic circuit gain (MCG). It was determined that the MCG of the MFC is not directly related to the absolute values of its parameters but rather to their ratios. Simulation analyses evaluated the impact of these parameter ratios on both the MCG and its spatial distribution uniformity, leading to the formulation of MFC design optimization principles. Building on these simulation-derived principles, several MFCs were fabricated using the 1J85 material, and an experimental platform was established to validate the simulation findings. The fabricated MFCs achieved an MCG of 7.325 times. Based on the previously developed TMR devices, a detection sensitivity of 2.46 nT/$\sqrt{\mathrm{Hz}}$ @1Hz was obtained. By optimizing parameter configurations, this work provides theoretical guidance for further enhancing the performance of TMR sensors in magnetic field measurements. Full article

Mechanical defects and sensor failures can substantially undermine the reliability of low-cost sensors, especially in applications where measurement inaccuracies or malfunctions may lead to critical outcomes, including system control disruptions, emergency scenarios, or safety hazards. To overcome these challenges, this paper presents a novel Self-X architecture with sensor redundancy, which incorporates dynamic calibration based on multidimensional mapping. By extracting reliable sensor readings from imperfect or defective sensors, the system utilizes Self-X principles to dynamically adapt and optimize performance. The approach is initially validated on synthetic data from tunnel magnetoresistance (TMR) sensors to facilitate method analysis and comparison. Additionally, a physical measurement setup capable of controlled fault injection is described, highlighting practical validation scenarios and ensuring the realism of synthesized fault conditions. The study highlights a wide range of potential TMR sensor failures that compromise long-term system reliability and demonstrates how multidimensional mapping effectively mitigates both static and dynamic errors, including offset, amplitude imbalance, phase shift, mechanical misalignments, and other issues. Initially, four individual TMR sensors exhibited mean absolute error (MAE) of 4.709°, 5.632°, 2.956°, and 1.749°, respectively. To rigorously evaluate various dimensionality reduction (DR) methods, benchmark criteria were introduced, offering insights into the relative improvements in sensor array accuracy. On average, MAE was reduced by more than 80% across sensor combinations. A clear quantitative trend was observed: for instance, the MAE decreases from 4.7°–5.6° for single sensors to 0.111° when the factor analysis method was applied to four sensors. This demonstrates the concrete benefit of sensor redundancy and DR algorithms for creating robust, fault-tolerant measurement systems. Full article

In response to the accurate positioning issue for high-speed moving lens groups in rapid zoom optical lenses with voice coil motors (VCMs), we demonstrate a positioning system design based on tunnel magnetoresistance sensors. The equivalent magnetic charge method and finite element method (FEM) simulations were utilized to compute the magnetic field distribution of the magnetic grating encoder. Based on analytical computation, the optimal air gap δ_S between the sensor and magnetic grating is determined to be δ_S = 0.15 mm, which balances magnetic flux density amplitude and total harmonic distortion. In addition, a simplified fitting model is proposed to reduce computational complexity. We quantify the magnetic interference of VCM through three-dimensional flux leakage mapping by FEM analysis, deriving an optimal sensor position O_S, with a 24 mm y-offset and 20 mm z-offset relative to the VCM’s origin O_V. The position error caused by interference remains below 5 μm with maximum deviations at trajectory endpoints of the moving group. The original signal output is processed and corrected, and eventually, the measured displacement exhibits a linear relationship with actual displacement. Our study provides a comprehensive framework for the design and optimization of magnetic positioning systems in optical applications with electromagnetic motors. Full article

Accurate measurement of magnetic fields holds immense significance across various disciplines, such as IC circuit measurement, geological exploration, and aerospace. The sensitivity and noise parameters of magnetic field sensors play a vital role in detecting minute fluctuations in magnetic fields. However, the current detection capability of tunneling magnetoresistance (TMR) is insufficient to meet the requirements for weak magnetic field measurement. This study investigates the impact of structural and fabrication parameters on the performance of TMR sensors. We fabricated series-connected TMR sensors with varying long-axis lengths of the elliptical cross-section and adjusted their performance by modifying annealing magnetic fields and magnetic field bias along the easy axis. The results demonstrate that TMR sensitivity decreases with increasing long-axis length, increases initially and then decreases with an annealing magnetic field, and decreases with a higher bias magnetic field along the easy axis. The voltage noise level of TMR sensors decreases as the long-axis length increases. Notably, the detection capability of TMR sensors exhibits a non-monotonic dependence on long-axis length. Moreover, we optimized the hysteresis of TMR sensors by applying a magnetic field bias along the easy axis. When the bias along the easy axis reached 16 Oe or −40 Oe, the hysteresis level was reduced to below 0.5 Oe. After encapsulating the TMR devices into a full Wheatstone bridge structure, we achieved a detection capability of 17 nT/$\sqrt{\mathrm{Hz}}$@1Hz. This study highlights that the detection capability of TMR devices is jointly influenced by fabrication parameters. By optimizing parameter configuration, this work provides theoretical guidance for further enhancing the performance of TMR devices in magnetic field measurements. Full article

Establishing a maintenance-free current sensing network across the entire power grid to facilitate wide-area online monitoring is crucial for realizing a smart grid. However, distribution networks (DNs) frequently lack effective real-time current monitoring owing to the complexity of load types, extensive line distribution, and numerous branches. In this study, we propose a high-precision, self-powered online current monitoring system that integrates a TMR sensors array module, a main control module, a current transformer (CT) power harvesting module, and current online monitoring software. The TMR sensors array module boasts a measurement range of 0–300 A and a high sensitivity of 25.38 mV/A. To address wire eccentricity errors in array sensors, we develop a neural network-based correction algorithm, which identifies wire positions and applies correction coefficients, achieving high accuracy with an average error of 1.23%. Current data are wirelessly transmitted to software terminals via 4G communication for remote monitoring. Furthermore, the CT power harvesting module converts magnetic energy from the power grid into electrical energy, ensuring that the system is self-powered. Validation through continuous 24-h monitoring of DNs demonstrates the system’s high precision and stability. This work presents an effective solution for high-accuracy online current monitoring in DNs. Full article

With the rapid development of current sensor technology, tunnel magnetoresistance (TMR) current sensors have been widely adopted in industrial detection due to their high sensitivity, excellent linearity, and broad measurement range. This study focuses on closed-loop TMR current sensors, utilizing COMSOL Multiphysics 6.2 software and the finite element method to conduct an in-depth analysis of structural parameters affecting sensor sensitivity. A novel magnetic shielding package architecture is proposed and designed. Simulation results demonstrate that the shielding efficiency of this structure improves by 44.3% compared to a single magnetic ring under a stray magnetic field of 0.1 mT along the sensing axis. At the same time, the measurement accuracy is 2.1 times higher than that of traditional structures. Current detection experiments conducted in a strong magnetic field environment further validate that the shielding package effectively suppresses external electromagnetic interference, significantly enhancing sensor stability and measurement accuracy. This research provides important theoretical and practical insights for applying high-precision TMR current sensors in complex electromagnetic environments. Full article

To meet the demand for high-precision, high-resolution measurement of weak currents in smart grids, this article presents the design of a current sensor based on the tunneling magnetoresistance (TMR) effect. To improve the detection accuracy of the sensor, this design adopts a low-noise, high-sensitivity TMR chip as its chip selection; in the sensor circuit, a high-linearity interface circuit is used to eliminate fixed bias; and a magnetic flux concentrator is used to improve sensitivity and anti-interference capability. Experimental results indicate that the sensor achieves a sensitivity of 29.4 mV/V/mA, a linearity of 0.19%, and an accuracy of 0.045% within a ±100 mA range, supporting current measurement from DC up to 10.5 kHz. The proposed sensor demonstrates several advantages, including a wide measurement range, high accuracy, high resolution, and non-invasive measurement capability, making it well suited for weak current detection in smart grid applications. Full article

Surface quality control of hot-dip galvanized sheets is a critical research topic in the metallurgical industry. Zinc dross, the most common surface defect in the hot-dip galvanizing process, significantly affects the sheet’s service performance. In this manuscript, a novel magnetic flux leakage (MFL) detection method was proposed to detect zinc dross defects on the surface of hot-dip galvanized steel sheets. Instead of using exciting coils in traditional methods, a tiny permanent magnet with a millimeter magnitude was employed to reduce the size and weight of the equipment. Additionally, a high-precision tunnel magnetoresistance (TMR) sensor with a sensitivity of 300 mV/V/Oe was selected to achieve higher detection accuracy. The experimental setup was established, and the x-axis direction (sample movement direction) was determined as the best measurement axis by vector analysis through experiments and numerical simulation. The detection results indicate that this novel MFL detection method could detect industrial zinc dross with an equivalent size of 400 μm, with high signal repeatability and signal-to-noise ratio. In the range of 0–1200 mm/s, the detection speed has almost no effect on the measurement signal, which indicates that this novel method has higher adaptability to various conditions. The multi-path scanning method with a single probe was used to simulate the array measurement to detect a rectangular area of 30 × 60 mm. Ten zinc dross defects were detected across eight measurement paths with 4 mm intervals, and the positions of these zinc dross defects were successfully reconstructed. The research results indicate that this novel MFL detection method is simple and feasible. Furthermore, the implementation of array measurements provides valuable guidance for subsequent in-depth research and potential industrial applications in the future. Full article

Tunnel magnetoresistance (TMR) sensors, known for their high sensitivity, efficiency, and compact size, are ideal for detecting weak currents, particularly leakage currents in smart grids. However, temperature variations can negatively impact their accuracy. This work investigates the effects of temperature variations on measurement accuracy. We analyzed the operating principles and temperature characteristics of TMR sensors and proposed a high-precision, software-based temperature compensation method using cubic spline interpolation combined with polynomial regression and zero-point self-calibration. Additionally, a field-programmable gate array (FPGA)-based temperature compensation circuit was designed and implemented. An experimental platform was established to comprehensively evaluate the sensor’s performance under various temperature conditions. Experimental results demonstrate that this method significantly enhances the sensor’s temperature stability, reduces the sensitivity temperature drift coefficient, and improves zero-point drift stability, outperforming other compensation methods. After compensation, the sensor’s measurement accuracy in complex temperature environments is substantially improved, enabling effective weak current detection in smart grids across diverse environments. Full article

The sensitivity of Tunnel Magnetoresistance (TMR) sensors is characterized by significant temperature drift and poor sensitivity drift repeatability, which severely impairs measurement accuracy. Conventional temperature compensation techniques are often hindered by low compensation precision, inadequate real-time performance, and an inability to effectively address the issue of poor repeatability in temperature drift characteristics. To overcome these challenges, this paper introduces a novel method for suppressing temperature drift in TMR sensors. In this method, an alternating reference magnetic field is applied to TMR sensors, and the output amplitude at the frequency of the reference magnetic field is calculated to compensate the sensitivity temperature drift in real time. Temperature characteristic tests were conducted in a non-magnetic temperature test chamber, and the results revealed that the proposed method significantly reduced the TMR sensitivity drift coefficient from 985.39 ppm/°C to 59.08 ppm/°C. Additionally, the repeatability of sensitivity temperature characteristic curves was enhanced, with a reduction in root mean square error from 0.84 to 0.21. This approach effectively mitigates temperature-induced sensitivity drift without necessitating the use of a temperature sensor, and has the advantages of real-time performance and repeatability, providing a new approach for the high-precision temperature drift suppression of TMR. Full article

Current sensors play a vital role in power systems, industrial production, smart devices and other fields, which can provide critical current information in the systems for the safety and efficiency managements. The development of magneto-resistive effect technology in recent years expedites the research process of the current sensors in industrial-level applications. In the review, starting with the development status of the current sensors, the physical mechanisms of the relevant magneto-resistive effects and their early applications as the current sensors are introduced. Several design methods of the magnetic sensors, as well as their merits and shortcomings, are summarized. The performance parameters of the magnetic sensors based on AMR, GMR, TMR and Hall effects are reviewed, including the front-end amplification circuits and conditioning circuits. The industrial applications of the current sensors in the fields of automobiles and photovoltaic inverters are enumerated. The criterions for the current sensors to be used in different scenarios are discussed. In the future, it is imperative to continue the research and development of novel current sensors in order to satisfy the increasingly stringent demands of the industrial developments, in terms of the performance, cost and reliability of the current sensors. Full article

This study proposes a high-resolution rotation-measuring system for miniaturized MEMS ultrasonic motors using tunneling magnetoresistance (TMR) sensors for the first time. Initially, the architecture and principle of the rotation-measuring system are described in detail. Then, the finite element simulation is implemented to determine the miniaturized permanent magnet’s residual magnetization, dimensions, and TMR sensor position. Finally, the experiments are implemented to evaluate the performance. Using calibration based on a high-precision servo motor, it is found that the relationship between the output and rotational angle is highly linear and immune to the rotor’s out-of-plane movement. Meanwhile, the angle-detecting resolution is higher than 0.1°. After the calibration, the continuous rotation of the MEMS ultrasonic motor is tested. It is found that the angle testing result varies with a period close to 360°, which indicates that the rotation-measuring system has successfully detected the motor’s rotation. Full article

The main objective of the work is to investigate the capacity of a single magnetoresistance (MR) element to measure AC electrical currents. An instrumentation system is presented to characterize individually the four active elements of an MR bridge current sensor preserving their internal connections. The system suggests the possibility to sense electrical currents using only one element of the bridge opening the way to design new MR sensors based on this concept. Sensitivity, offset and non-linearity deviation were obtained using bridges of tunnel (TMR)- and giant (GMR)-based MR technologies. The single element embedded in a Wheatstone bridge configuration is used for practical current measurements in a 50 Hz line. An electronic circuitry is proposed to measure alternating (AC) currents with a single MR element, including a lock-in amplifier and an interface to properly convert the signal to its root mean square (rms) value with a resolution of 250 mA peak in the 125 A range. Full article