Electric Sensor Research Articles

Using Rapid Prototyping to Develop a Cell-Based Platform with Electrical Impedance Sensor Membranes for In Vitro RPMI2650 Nasal Nanotoxicology Monitoring.

Due to advances in additive manufacturing and prototyping, affordable and rapid microfluidic sensor-integrated assays can be fabricated using additive manufacturing, xurography and electrode shadow masking to create versatile platform technologies aimed toward qualitative assessment of acute cytotoxic or cytolytic events using stand-alone biochip platforms in the context of environmental risk assessment. In the current study, we established a nasal mucosa biosensing platform using RPMI2650 mucosa cells inside a membrane-integrated impedance-sensing biochip using exclusively rapid prototyping technologies. In a final proof-of-concept, we applied this biosensing platform to create human cell models of nasal mucosa for monitoring the acute cytotoxic effect of zinc oxide reference nanoparticles. Our data generated with the biochip platform successfully monitored the acute toxicity and cytolytic activity of 6 mM zinc oxide nanoparticles, which was non-invasively monitored as a negative impedance slope on nasal epithelial models, demonstrating the feasibility of rapid prototyping technologies such as additive manufacturing and xurography for cell-based platform development.

Bionic tribo-sensors with sweat and smudge-resistant as electronic skin for personal authentication

The increasing prevalence of the internet in our daily lives has made cybersecurity and banking security crucial concerns. Traditional methods such as passwords, fingerprints, and face recognition are becoming replicable and susceptible to hacking. To address this issue, we developed innovative biometric keystroke dynamics for personal authentication utilizing friction electric sensors. A single-electrode triboelectric nanogenerator utilizes the skin as a positive friction layer, allowing direct contact with the sensor. This arrangement enables the detection of subtle mechanical changes during pressing. To mitigate the impact of sweat and organic pollutants, a bionic rose petal friction layer is incorporated, ensuring consistent output and long-term effectiveness. The sensor efficiently converts mechanical keystroke actions into electrical signals for individuals and transmits them to an artificial neural network-based AI system. By utilizing a self-powered sweat- and dirt-proof biometric authentication system, along with the LSTM neural network algorithm, we have achieved an impressive accuracy rate of 97%. This system provides a promising security layer against password cracking and user privacy vulnerabilities.

A Combined Magnetoelectric Sensor Array and MRI-Based Human Head Model for Biomagnetic FEM Simulation and Sensor Crosstalk Analysis.

Magnetoelectric (ME) magnetic field sensors are novel sensing devices of great interest in the field of biomagnetic measurements. We investigate the influence of magnetic crosstalk and the linearity of the response of ME sensors in different array and excitation configurations. To achieve this aim, we introduce a combined multiscale 3D finite-element method (FEM) model consisting of an array of 15 ME sensors and an MRI-based human head model with three approximated compartments of biological tissues for skin, skull, and white matter. A linearized material model at the small-signal working point is assumed. We apply homogeneous magnetic fields and perform inhomogeneous magnetic field excitation for the ME sensors by placing an electric point dipole source inside the head. Our findings indicate significant magnetic crosstalk between adjacent sensors leading down to a 15.6% lower magnetic response at a close distance of 5 mm and an increasing sensor response with diminishing crosstalk effects at increasing distances up to 5 cm. The outermost sensors in the array exhibit significantly less crosstalk than the sensors located in the center of the array, and the vertically adjacent sensors exhibit a stronger crosstalk effect than the horizontally adjacent ones. Furthermore, we calculate the ratio between the electric and magnetic sensor responses as the sensitivity value and find near-constant sensitivities for each sensor, confirming a linear relationship despite magnetic crosstalk and the potential to simulate excitation sources and sensor responses independently.

Role of natural rubber structure in the electrical conductivity and strain sensor performance of natural rubber/carbon nanotube nanocomposites stabilized by sodium alginate

Strain-sensitive sensors utilizing nanocomposites of natural rubber (NR) were produced through latex mixing technology, employing different varieties of NR, namely, unmodified NR and epoxidized NR with 25 and 50 mol% epoxidized natural rubber (ENR25 and ENR50) respectively. A linear polysaccharide, sodium alginate (Alg), was used as an effective dispersing agent. This work revealed that the polar functional group on the rubber structure showed a positive impact on the dispersion state of carbon nanotubes (CNTs) in the nanocomposite suspensions. The incorporation of Alg as a dispersing agent in rubber nanocomposites remarkably improved the uniformity and overall performance of the nanocomposite suspensions. The results demonstrated the critical role of the polar functional group on the NR molecules in achieving an outstanding electrical conductivity of 102 S/cm. In addition, the mechanical properties were dramatically improved with the introduction of Alg into NR, ENR25, and ENR50 filled with CNTs. Alg improved the electrical conductivity and strain sensitivity of the rubber nanocomposites and the variation of R/R0, demonstrating its beneficial effect on the strain sensor.

Realtime monitoring of thrombus formation in vivo using a self-reporting vascular access graft

BackgroundChronic kidney disease (CKD) affects 10% of the global population costing over a hundred billion dollars per annum and leading to increased risk of cardiovascular disease. Many patients with CKD require regular haemodialyses. Synthetic arteriovenous grafts (AVG) are increasingly used to provide rapid vascular connection for dialysis. Initially, they have excellent patency rates but are critically limited by neointimal hyperplasia at the venous anastomosis, which drives subsequent thrombosis, graft failure and death.MethodsHere, we describe a system in which electrical impedance spectroscopy sensors are incorporated circumferentially into the wall of a synthetic arteriovenous graft. This is combined with an implantable radiotelemetry system for data transmission outside the patient. The system was tested using monolayers of endothelial and smooth muscle cells as well as swine blood and clots with explanted human carotid artery plaques. Sensor testing was then performed in vitro and the device was implanted in vivo in female swine.ResultsThe device can wirelessly report the accumulation of biological material, both cells and blood. Differences are also detected when comparing controls with pathological atheroma. In swine differences between blockage formation in a graft were remotely obtained and wireless reported.ConclusionsCombining electrical impedance spectroscopy and an implantable radiotelemetry system enables graft surveillance. This has the potential to be used for early detection of venous stenosis and blood clot formation in real-time in vivo. In principle, the concept could apply to other cardiovascular diseases and vascular implantable devices.

An Approach to Using Electrical Impedance Myography Signal Sensors to Assess Morphofunctional Changes in Tissue during Muscle Contraction.

This present work is aimed at conducting fundamental and exploratory studies of the mechanisms of electrical impedance signal formation. This paper also considers morphofunctional changes in forearm tissues during the performance of basic hand actions. For this purpose, the existing research benches were modernized to conduct experiments of mapping forearm muscle activity by electrode systems on the basis of complexing the electrical impedance signals and electromyography signals and recording electrode systems' pressing force using force transducers. Studies were carried out with the involvement of healthy volunteers in the implementation of vertical movement of the electrode system and ultrasound transducer when the subject's upper limb was positioned in the bed of the stand while performing basic hand actions in order to identify the relationship between the morphofunctional activity of the upper limb muscles and the recorded parameters of the electro-impedance myography signal. On the basis of the results of the studies, including complex measurements of neuromuscular activity on healthy volunteers such as the signals of electro-impedance myography and pressing force, analyses of the morphofunctional changes in tissues during action performance on the basis of ultrasound and MRI studies and the factors influencing the recorded signals of electro-impedance myography are described. The results are of fundamental importance and will enable reproducible electro-impedance myography signals, which, in turn, allow improved anthropomorphic control.

Multi-fault detection and diagnosis method for battery packs based on statistical analysis

Rapid and accurate battery fault diagnosis and distinction is of great importance in electrical vehicles and electrochemical energy storage system. However, misdiagnosis and missed diagnosis happened occasionally. In this paper, a statistical analysis-based multi-fault diagnosis method is proposed to detect and localize short circuit faults, electrical connection faults and voltage sensor faults in LFP battery packs. This method uses non-redundant interleaved voltage measurement topology to detect battery voltages, where every voltage sensor measures the sum of two neighboring batteries and one connection resistor between them. The statistical analysis method sets detection thresholds based on the battery operating data, and captures fault characteristics by analyzing abnormal changes in battery voltage unrelated to current. Theoretical analysis and tests verified that this method can diagnose these three kinds of faults. Sensor faults of excessive error and data sticking can also be distinguished.

Improving vineyard irrigation efficiency with soil water sensors

Improving vineyard irrigation efficiency with soil water sensors Using soil water sensors to automatically schedule irrigation in winegrape vineyards offers the potential for growers to enhance water use productivity under warmer climate conditions. The use of electrical soil water sensors for improving crop water use efficiency is an emerging trend in agricultural regions of the world where irrigation is vital for sustainable food production. This advancement uses solar powered electronic capacitance probes to activate irrigation in real time for maintaining a desired level of soil water content needed by a particular crop.

50-Channel Ionoacoustic Sensor for 60 MeV Proton Beam Characterization in Hadron Therapy Applications

This paper presents the design of a piezoelectric multichannel sensor optimized for sensing weak ionoacoustic signals generated at the Bragg peak (BP) of pulsed proton beams, with interesting possible applications in real-time monitoring of oncological hadron therapy treatments. To overcome current single-channel detector limitations and acquire the weak acoustic signals of clinical scenarios (60–200 MeV proton energy and few mGy dose deposition), the hereby presented detector overcomes the state-of-the-art approach (based on time-domain correlation i.e., averaging different beam pulses) by using spatial correlation (i.e., averaging signals from different detector channels) to increase the SNR without increasing the delivered dose. The detector design is tailored around the experimental environment characteristics (signal amplitude, signal frequency, relative BP-detector position) of a clinical proton beam (60 MeV, 2 mGy/pulse dose deposition). The detector design was characterized by a complete cross-domain simulation of the physical (proton beam), acoustic (wave propagation) and electrical (sensor and electronics frequency response and noise) environments. It achieves a clear 10 dB single-pulse SNR (2 mGy total dose) and allows to locate the BP with 125 μm precision (< 3% w.r.t. the particle range). Finally, the detector was experimentally validated by a piezoelectric acoustic testbench and has shown the capability to localize an acoustic source in 2D with sub-millimeter accuracy by using a multilateration-based BP detection algorithm.

In the Direction of an Artificial Intelligence-Enabled Monitoring Platform for Concrete Structures.

In a seismic context, it is fundamental to deploy distributed sensor networks for Structural Health Monitoring (SHM). Indeed, regularly gathering data from a structure/infrastructure gives insight on the structural health status, and Artificial Intelligence (AI) technologies can help in exploiting this information to generate early warnings useful for decision-making purposes. With a perspective of developing a remote monitoring platform for the built environment in a seismic context, the authors tested self-sensing concrete beams in loading tests, focusing on the measured electrical impedance. The formed cracks were objectively assessed through a vision-based system. Also, a comparative analysis of AI-based and statistical prediction methods, including Prophet, ARIMA, and SARIMAX, was conducted for predicting electrical impedance. Results show that the real part of electrical impedance is highly correlated with the applied load (Pearson's correlation coefficient > 0.9); hence, the piezoresistive ability of the manufactured specimens has been confirmed. Concerning prediction methods, the superiority of the Prophet model over statistical techniques was demonstrated (Mean Absolute Percentage Error, MAPE < 1.00%). Thus, the exploitation of electrical impedance sensors, vision-based systems, and AI technologies can be significant to enhance SHM and maintenance needs prediction in the built environment.

A Review of Advances in Graphene Quantum Dots: From Preparation and Modification Methods to Application

Graphene quantum dot (GQD) is a new type of carbon nanometer material. In addition to the excellent properties of graphene, it is superior due to the quantum limit effect and edge effect. Because of its advantages such as water solution, strong fluorescent, small size, and low biological toxicity, it has important application potential in various fields, especially in sensors and biomedical areas, which are mainly used as optical electrical sensors as well as in biological imaging and tumor therapy. In addition, GQDs have very important characteristics, such as optical and electrical properties. There are many preparation methods, divided into top-down and bottom-up methods, which have different advantages and disadvantages, respectively. In addition, the modification methods include heterogeneous doping, surface heterogeneity, etc. There are still many challenges in developing GQDs. For example, the synthesis steps are still hard to conduct, but as the inquiry continues to deepen, GQDs will be revolutionary materials in the future. In this work, the literature concerning research progress on GQDs has been reviewed and summarized, while the key challenges of their application have been pointed out, which may bring new insights to the application of GQDs.

Noninvasive imaging of 4D electrical activation patterns of uterine peristalsis during normal menstrual cycles

Uterine peristalsis, characterized by spontaneous slow-wave contractions of the subendometrial layer of the uterine myometrium, occurs throughout the menstrual cycle. Disruptions in peristalsis patterns may occur in women experiencing abnormal uterine bleeding, endometriosis, and infertility. Current tools to measure uterine peristalsis in humans have limitations that hamper their research or clinical utility. Here, we developed an electrophysiological imaging system with wearable electrical sensors to noninvasively quantify the four-dimensional electrical activation pattern during human uterine peristalsis with high spatial and temporal resolution and coverage. To demonstrate capabilities of this new imaging system, we enrolled 26 pre-menopausal participants ages 18–40 years old with regular menstrual cycles (25–34 days in length) and normal gynecologic anatomy. Participants initially underwent magnetic resonance imaging to obtain the body-uterus geometry. Then, during each of the four phases of a single menstrual cycle, patients underwent noninvasive electrical recording for 30 min. We measured uterine peristalsis frequency, direction, duration, magnitude, and power and found that these parameters differed in different phases of the menstrual cycle. Future use of this uterine peristalsis imaging system may advance our understanding of the role of uterine peristalsis in maintaining normal uterine function and contributing to gynecological pathophysiology.

Сравнительное исследование двойного и сдвоенного электроиндукционных сферических датчиков напряженности электрического поля

The work provides a comparative study of double and dual electric field strength sensors. The comparison examined the design, technological and metrological parameters of the sensors, as well as the complexity of their measuring circuits. Research has revealed similarities in the design and technological parameters of the sensors and differences in metrological characteristics and the complexity of the measuring circuits. In terms of metrological characteristics, dual sensors are significantly superior to double ones. It has been established that a dual sensor having sensitive elements with angular dimensions 1=46,38 , and 2=90 , has a smaller error due to field inhomogeneity. The error does not exceed  ±2,76 % in the spatial measurement range 0a1. With the same error, double sensors can only be used in a limited spatial measurement range of 0a0,89. It is shown that dual sensors are superior to dual sensors in terms of metrological parameters. This indicates the advisability of their use.

Optical fiber high-temperature pressure sensor with weak temperature sensitivity

In aerospace, petrochemical, gas turbines and other high-temperature environments, pressure measurement of equipment has always been a challenge to be solved. The electrical high temperature pressure sensor has the problem of component failure in high temperature environment, and it is difficult to use in the high temperature environment for a long time. The detection device of the optical fiber sensor does not include electrical components, so it has the advantages of high working temperature, high measurement accuracy, anti-electromagnetic interference and so on. In order to use a sensor to measure pressure in high temperature environment, a temperature-weakly sensitive optical fiber micro-electro-mechanical system (MEMS) pressure sensing technology is proposed. The technique uses extrisic Fabry-Pérot interference (EFPI) model. It uses the MEMS pressure chip to passively modulate the optical signal of the interference, and then realizes the pressure signal measurement. Among them, MEMS pressure sensitive chip is the core component of the sensor. The MEMS pressure sensitive chip adopts the design method of all solid state vacuum absolute pressure. Change in environmental pressure will deform the membrane. This phenomenon can cause change in the cavity of the EFPI cavity. Therefore, stress information can be obtained by measuring changes in EFPI cavity. The thermal stress and temperature parasitical response introduced by thermal expansion of the material are calculated by simulation. The influence of temperature signal on chip displacement is analyzed by the above results. On this basis, a prototype of high temperature pressure sensor is developed by combining the sub-micron white light interference response technology and low thermal stress packaging technology. In order to test the ability of the sensor to implement actual measurement, this paper carry out the pressure test and high temperature test respectively. When the pressure changes from 0 kPa to 100 kPa, the spectral intensity of the sensor output has a linear relationship with the pressure. During the temperature changing from 20–400 ℃, the spectral intensity of the sensor output does not change significantly. The experimental test results show that the pressure measurement of 0–100 kPa can be satisfied in the range of 20–400 ℃, and the measurement error introduced by temperature change is less than 4%. Therefore, the fiber pressure sensor can be used to measure the pressure in high temperature environment.

Research on self-calibration method of electric field time-grating angular displacement sensor based on error function phase shift

Research on self-calibration method of electric field time-grating angular displacement sensor based on error function phase shift

Bioinspired colloidal crystal hydrogel pressure sensors with Janus wettability for uterus cervical canal tension perception.

The pursuit of flexible, sensitive, and cost-effective pressure sensors plays a pivotal role in medical diagnostics, particularly in the domain of cervical health monitoring. However, significant challenges remain in the economical production of flexible piezoresistive materials and the integration of microstructures aimed at enhancing sensor sensitivity. This urge highlights the use of innovative, stable hydrogel films that demonstrate robust adherence to soft biological tissues, thereby enabling prolonged bio-signal monitoring. In this study, we introduce an innovative integration of a flexible pressure electrical signal sensor with structural color hydrogel scaffolds. This integration leverages the tunability of the inverse opal structure to fine-tune the scaffold's adherence to the endocervical wall under varying environmental conditions and to amplify the sensitivity of pressure measurements. Our findings indicate that this novel approach holds promise for substantial enhancements in the manufacturing and functional capabilities of cervical pressure sensors, potentially revolutionizing personalized medical treatments and improving patient monitoring.

An integrated FAHP and TOPSIS for supplier selection under uncertainty: a case study in electrical explosion protection and sensor company

An integrated FAHP and TOPSIS for supplier selection under uncertainty: a case study in electrical explosion protection and sensor company

An integrated FAHP and TOPSIS for supplier selection under uncertainty: a case study in Electrical Explosion Protection and Sensor company

An integrated FAHP and TOPSIS for supplier selection under uncertainty: a case study in Electrical Explosion Protection and Sensor company

Biomimetic photonic crystal double-network hydrogel for visual and electrical dual signal bluetooth-enabled wearable sensor

The photonic crystal wearable sensor which has visual and electrical dual signal outputs is successfully developed.

Analysis of Electric Sensor for Space Detectors: Mass Spectrometer, Particle Detector and CMOS/CCD Sensor

As a matter of fact, with the participation of government agencies and the exploration of private enterprises, space exploration is undergoing rapid development as well as change in recent years. With this in mind, these trends will continue to promote human exploration and utilization of space, providing more opportunities for scientific research, commercial applications and exploration. In order to realize accuracy observation, high precision detectors are necessary to be developed and implemented. To be specific, a large number of electric sensors are applied on the space detectors, including mass spectrometer, particle detector as well as CMOS/CCD image sensor, etc. On this basis, this paper presents the principles, structures and applications of these three electric sensors in detail. According to the analysis, this study also analyzes the existing shortcomings of the state-of-art facilities as well as proposes future developments. Overall, these results shed light on guiding further exploration of space detectors.