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Advanced Electromagnetic Sensors in Environmental, Industrial and Medical Applications II
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Advanced Electromagnetic Sensors in Environmental, Industrial and Medical Applications II

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 50362

Special Issue Editors

Prof. Dr. Tomasz Rymarczyk

E-Mail Website
Guest Editor
Institute of Computer Science and Innovative Technologies, WSEI University, Lublin, Poland
Interests: electromagnetism; energy efficiency; tomography; artificial intelligence; machine learning
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Ewa Korzeniewska

E-Mail Website
Guest Editor
Vice-President of Polish Society of Applied Electromagnetism, Faculty of Electrical, Electronic, Computer and Control Engineering, Lodz University of Technology, Stefanowskiego 18/22, 90-924 Łódź, Poland
Interests: materials science; textronics; wearable electronics; thin films; electromagnetic field applications; electrical engineering systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Following the success of the previous Special Issue “Advanced Electromagnetic Sensors in Environmental, Industrial and Medical Applications” (https://www.mdpi.com/journal/sensors/special_issues/Electromagnetic_Sensors_Applications), we are pleased to announce the next in the series, entitled “Advanced Electromagnetic Sensors in Environmental, Industrial and Medical Applications II”.

This Special Issue aims to provide a comprehensive overview of current changes in the use of electromagnetism in new solutions and computational methods in environmental, industrial, medical, tomographic and IT applications, including mathematical aspects. In this Special Issue, full research articles, reviews and highly rated manuscripts will be published. The main focus will be on interdisciplinary work and the gathering of research fields, including experimental, theoretical and computational work, artificial intelligence, and the analysis and interpretation of data.

Prof. Dr. Tomasz Rymarczyk
Prof. Dr. Ewa Korzeniewska
Guest Editors

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Keywords

  • Smart Sensors
  • Transducers
  • Sensing Technologies
  • Electromagnetic Sensing
  • Soft Sensors
  • RFID Sensors
  • Wearable Sensors
  • Nondestructive Testing
  • Inverse Problems
  • Tomography
  • Artificial Intelligence
  • Machine Learning
  • Deep Learning
  • Medical Imaging
  • Image Analysis
  • Data Analysis
  • Numerical Calculation
  • Internet of Things
  • Industry 4.0

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Published Papers (17 papers)

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Research

19 pages, 4639 KiB  
Article
Electromagnetic Wave Absorption in the Human Head: A Virtual Sensor Based on a Deep-Learning Model
by Paolo Di Barba, Łukasz Januszkiewicz, Jarosław Kawecki and Maria Evelina Mognaschi
Sensors 2023, 23(6), 3131; https://doi.org/10.3390/s23063131 - 15 Mar 2023
Cited by 2 | Viewed by 2790
Abstract
Determining the amount of electromagnetic wave energy absorbed by the human body is an important issue in the analysis of wireless systems. Typically, numerical methods based on Maxwell’s equations and numerical models of the body are used for this purpose. This approach is [...] Read more.
Determining the amount of electromagnetic wave energy absorbed by the human body is an important issue in the analysis of wireless systems. Typically, numerical methods based on Maxwell’s equations and numerical models of the body are used for this purpose. This approach is time-consuming, especially in the case of high frequencies, for which a fine discretization of the model should be used. In this paper, the surrogate model of electromagnetic wave absorption in human body, utilizing Deep-Learning, is proposed. In particular, a family of data from finite-difference time-domain analyses makes it possible to train a Convolutional Neural Network (CNN), in view of recovering the average and maximum power density in the cross-section region of the human head at the frequency of 3.5 GHz. The developed method allows for quick determination of the average and maximum power density for the area of the entire head and eyeball areas. The results obtained in this way are similar to those obtained by the method based on Maxwell’s equations. Full article
(This article belongs to the Special Issue Advanced Electromagnetic Sensors in Environmental, Industrial and Medical Applications II)
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22 pages, 2753 KiB  
Article
Prediction Models of Shielding Effectiveness of Carbon Fibre Reinforced Cement-Based Composites against Electromagnetic Interference
by Shilpa Narayanan, Yifan Zhang and Farhad Aslani
Sensors 2023, 23(4), 2084; https://doi.org/10.3390/s23042084 - 13 Feb 2023
Cited by 4 | Viewed by 2002
Abstract
With the rapid development of communication technology as well as a rapid rise in the usage of electronic devices, a growth of concerns over unintentional electromagnetic interference emitted by these devices has been witnessed. Pioneer researchers have deeply studied the relationship between the [...] Read more.
With the rapid development of communication technology as well as a rapid rise in the usage of electronic devices, a growth of concerns over unintentional electromagnetic interference emitted by these devices has been witnessed. Pioneer researchers have deeply studied the relationship between the shielding effectiveness and a few mixed design parameters for cementitious composites incoporating carbon fibres by conducting physical experiments. This paper, therefore, aims to develop and propose a series of prediction models for the shielding effectiveness of cementitious composites involving carbon fibres using frequency and mixed design parameters, such as the water-to-cement ratio, fibre content, sand-to-cement ratio and aspect ratio of the fibres. A multi-variable non-linear regression model and a backpropagation neural network (BPNN) model were developed to meet the different accuracy requirements as well as the complexity requirements. The results showed that the regression model reached an R2 of 0.88 with a root mean squared error (RMSE) of 2.3 dB for the testing set while the BPNN model had an R2 of 0.96 with an RMSE of 2.64 dB. Both models exhibited a sufficient prediction accuracy, and the results also supported that both the regression and the BPNN model are reasonable for such estimation. Full article
(This article belongs to the Special Issue Advanced Electromagnetic Sensors in Environmental, Industrial and Medical Applications II)
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14 pages, 3647 KiB  
Article
Effect of LED Lighting on Selected Quality Parameters of Electricity
by Agnieszka Wantuch and Michał Olesiak
Sensors 2023, 23(3), 1582; https://doi.org/10.3390/s23031582 - 1 Feb 2023
Cited by 4 | Viewed by 2994
Abstract
Recently, various technological light sources have appeared on the market. As a result, it is extremely important to evaluate the characteristics of the available lamps and the impact they may have on the power grid. This article presents regulations and standards for power [...] Read more.
Recently, various technological light sources have appeared on the market. As a result, it is extremely important to evaluate the characteristics of the available lamps and the impact they may have on the power grid. This article presents regulations and standards for power quality, including higher current and voltage harmonics, and analyzes three selected light-emitting diode lamps. The purpose of the study was to analyze the impact of LED lighting systems on the power quality (PQ) of the electric grid. The results of measurements of parameters determining the power quality of the electricity consumed by modern LED light sources used for room lighting are presented. Commercially available lamps and low-power power supplies (25 to 35 W) with an output current of 350 mA were used for the study. The current waveforms of selected lamps during their connection to the power grid, the results of harmonic emission tests, as well as the effect of increasing the load of selected DC power supplies (drivers) on THD, power factor (PF), and their efficiency are presented. The significant negative impact of power supply circuits in compact LED lamps on the power quality parameters of lighting circuits was demonstrated. The tested lamps significantly exceed the permissible limits of harmonics and THD. Test results have shown that LED lamps show significant savings in electricity consumption, but they behave as nonlinear loads. They generate high-frequency current harmonics, which can lead to degradation of power quality in the distribution network. Therefore, if the primary concern for the user is power quality rather than power savings, traditional incandescent lamps would be a much better choice. When using switched-mode power supplies, attention should be paid to their load rating. You should avoid using power supplies in the lower ranges of permissible load capacity. A more heavily loaded power supply has better performance due to power quality and efficiency. Full article
(This article belongs to the Special Issue Advanced Electromagnetic Sensors in Environmental, Industrial and Medical Applications II)
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22 pages, 5227 KiB  
Article
Application of Machine Learning Algorithms to the Discretization Problem in Wearable Electrical Tomography Imaging for Bladder Tracking
by Bartłomiej Baran, Edward Kozłowski, Dariusz Majerek, Tomasz Rymarczyk, Manuchehr Soleimani and Dariusz Wójcik
Sensors 2023, 23(3), 1553; https://doi.org/10.3390/s23031553 - 31 Jan 2023
Cited by 4 | Viewed by 2097
Abstract
The article presents the implementation of artificial intelligence algorithms for the problem of discretization in Electrical Impedance Tomography (EIT) adapted for urinary tract monitoring. The primary objective of discretization is to create a finite element mesh (FEM) classifier that will separate the inclusion [...] Read more.
The article presents the implementation of artificial intelligence algorithms for the problem of discretization in Electrical Impedance Tomography (EIT) adapted for urinary tract monitoring. The primary objective of discretization is to create a finite element mesh (FEM) classifier that will separate the inclusion elements from the background. In general, the classifier is designed to detect the area of elements belonging to an inclusion revealing the shape of that object. We show the adaptation of supervised learning methods such as logistic regression, decision trees, linear and quadratic discriminant analysis to the problem of tracking the urinary bladder using EIT. Our study focuses on developing and comparing various algorithms for discretization, which perfectly supplement methods for an inverse problem. The innovation of the presented solutions lies in the originally adapted algorithms for EIT allowing for the tracking of the bladder. We claim that a robust measurement solution with sensors and statistical methods can track the placement and shape change of the bladder, leading to effective information about the studied object. This article also shows the developed device, its functions and working principle. The development of such a device and accompanying information technology came about in response to particularly strong market demand for modern technical solutions for urinary tract rehabilitation. Full article
(This article belongs to the Special Issue Advanced Electromagnetic Sensors in Environmental, Industrial and Medical Applications II)
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13 pages, 6124 KiB  
Article
Field Modeling of the Influence of Defects Caused by Bending of Conductive Textronic Layers on Their Electrical Conductivity
by Stanisław Pawłowski, Jolanta Plewako and Ewa Korzeniewska
Sensors 2023, 23(3), 1487; https://doi.org/10.3390/s23031487 - 29 Jan 2023
Cited by 2 | Viewed by 1685
Abstract
One of the critical parameters of thin-film electrically conductive structures in wearable electronics systems is their conductivity. In the process of using such structures, especially during bending, defects and microcracks appear that affect their electrical parameters. Understanding these phenomena in the case of [...] Read more.
One of the critical parameters of thin-film electrically conductive structures in wearable electronics systems is their conductivity. In the process of using such structures, especially during bending, defects and microcracks appear that affect their electrical parameters. Understanding these phenomena in the case of thin layers made on flexible substrates, including textile ones, which are incorporated in sensors that monitor vital functions, is a key aspect when applying such solutions. Cracks and defects in such structures appearing during their use may be critical for the correct operation of such systems. In this study, the influence of defects resulting from the repeated bending of the conductive layer on its conductivity is analyzed. The anisotropic and partly stochastic characteristics of the defects are also taken into account. The defects are modeled in the form of broken lines, whose segments are generated in successive iterative steps, thus simulating the gradual wear of the layer material. The lengths and inclinations of these sections are determined randomly, which makes it possible to consider the irregularity of real defects of this type. It was found that near the percolation threshold, defects with a more irregular shape have a dominant effect on the reduction of conductivity due to the greater probability of their connection. The simulation results were compared with the experimental data. It was found that the dependence of the conductivity of the conductive layer on the number of bends is logarithmic. This allowed for the derivation of a formula linking the iteration number of the simulation procedure with the number of bends. Improving the strength of such layers is a technological challenge for researchers. Full article
(This article belongs to the Special Issue Advanced Electromagnetic Sensors in Environmental, Industrial and Medical Applications II)
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11 pages, 4003 KiB  
Article
Dependence of Sensitivity, Derivative of Transfer Curve and Current on Bias Voltage Magnitude and Polarity in Tunneling Magnetoresistance Sensors
by Łukasz Fuśnik, Bartłomiej Szafraniak, Jerzy Wrona, Susana Cardoso, Paulo. P. Freitas and Piotr Wiśniowski
Sensors 2023, 23(3), 1214; https://doi.org/10.3390/s23031214 - 20 Jan 2023
Cited by 1 | Viewed by 1787
Abstract
The sensitivity of tunneling magnetoresistance sensors is an important performance parameter. It depends on the derivative of resistance versus magnetic field (transfer curve) and the current and is expressed as the product of the two factors. Previous research has demonstrated that the bias [...] Read more.
The sensitivity of tunneling magnetoresistance sensors is an important performance parameter. It depends on the derivative of resistance versus magnetic field (transfer curve) and the current and is expressed as the product of the two factors. Previous research has demonstrated that the bias voltage has a significant impact on the sensitivity. However, no research has been conducted into the dependence of current and the derivative on bias voltage magnitude and polarity, and their contribution to the sensitivity. Thus, this paper investigates the dependence of sensitivity, derivative of resistance versus magnetic field curve and current on bias voltage magnitude and polarity in CoFeB/MgO/CoFeB-based tunneling magnetoresistance sensors with weak, strong and no voltage-controlled perpendicular magnetic anisotropy modification. It demonstrates that the sensitivity dependence on bias voltage for sensors with voltage controlled magnetic anisotropy modification showed no saturation up to 1 V. Moreover, the sensitivity asymmetry with respect to bias polarity changed significantly with bias, reaching a ratio of 6.7. Importantly, the contribution of current and the derivative of resistance versus magnetic field curve to the sensitivity showed a crossover. The current dominated the bias dependence of sensitivity below the crossover voltage and the derivative above the voltage. Furthermore, the crossover voltage in sensors without voltage controlled magnetic anisotropy modification did not depend on polarity, whereas in sensors with voltage controlled magnetic anisotropy modification, it appeared at significantly higher voltage under positive than negative polarity. Full article
(This article belongs to the Special Issue Advanced Electromagnetic Sensors in Environmental, Industrial and Medical Applications II)
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20 pages, 5437 KiB  
Article
Magnetic Induction Tomography: Separation of the Ill-Posed and Non-Linear Inverse Problem into a Series of Isolated and Less Demanding Subproblems
by Tatiana Schledewitz, Martin Klein and Dirk Rueter
Sensors 2023, 23(3), 1059; https://doi.org/10.3390/s23031059 - 17 Jan 2023
Cited by 2 | Viewed by 1883
Abstract
Magnetic induction tomography (MIT) is based on remotely excited eddy currents inside a measurement object. The conductivity distribution shapes the eddies, and their secondary fields are detected and used to reconstruct the conductivities. While the forward problem from given conductivities to detected signals [...] Read more.
Magnetic induction tomography (MIT) is based on remotely excited eddy currents inside a measurement object. The conductivity distribution shapes the eddies, and their secondary fields are detected and used to reconstruct the conductivities. While the forward problem from given conductivities to detected signals can be unambiguously simulated, the inverse problem from received signals back to searched conductivities is a non-linear ill-posed problem that compromises MIT and results in rather blurry imaging. An MIT inversion is commonly applied over the entire process (i.e., localized conductivities are directly determined from specific signal features), but this involves considerable computation. The present more theoretical work treats the inverse problem as a non-retroactive series of four individual subproblems, each one less difficult by itself. The decoupled tasks yield better insights and control and promote more efficient computation. The overall problem is divided into an ill-posed but linear problem for reconstructing eddy currents from given signals and a nonlinear but benign problem for reconstructing conductivities from given eddies. The separated approach is unsuitable for common and circular MIT designs, as it merely fits the data structure of a recently presented and planar 3D MIT realization for large biomedical phantoms. For this MIT scanner, in discretization, the number of unknown and independent eddy current elements reflects the number of ultimately searched conductivities. For clarity and better representation, representative 2D bodies are used here and measured at the depth of the 3D scanner. The overall difficulty is not substantially smaller or different than for 3D bodies. In summary, the linear problem from signals to eddies dominates the overall MIT performance. Full article
(This article belongs to the Special Issue Advanced Electromagnetic Sensors in Environmental, Industrial and Medical Applications II)
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21 pages, 4576 KiB  
Article
The Dependence of the Burning Process and Ignition Temperature of a Lithium Cell on Its State of Charge
by Andrzej Erd and Tomasz Ciszewski
Sensors 2023, 23(2), 753; https://doi.org/10.3390/s23020753 - 9 Jan 2023
Cited by 1 | Viewed by 1712
Abstract
Batteries and energy stores built with lithium-ion cells are potentially dangerous and can cause fires that are difficult to extinguish. Reducing the intensity of the fires and extending the time of their development may be of great importance for improving safety. The aim [...] Read more.
Batteries and energy stores built with lithium-ion cells are potentially dangerous and can cause fires that are difficult to extinguish. Reducing the intensity of the fires and extending the time of their development may be of great importance for improving safety. The aim of this work is to examine the influence of the state of charge (SOC) of a cell on susceptibility to ignition, and to analyze the course of the burning process. For this purpose, a special measuring station was built, where ignition was initiated and the course of combustion was observed. During the measurements, energy was supplied by heating a cell from the outside with a resistance heater while at the same time thermally insulating the cell from the environment. The measures of the course of the fire were the amount of energy supplied to the cell before ignition and the temperature changes during the fire. The tests proved the existence of significant differences in the amount of energy causing the ignition of cells. These differences result from changes in the SOC. Quantitative results are presented. The existence of differences in susceptibility to ignition can be used to change the construction of control algorithms for battery management systems (BMSs). Full article
(This article belongs to the Special Issue Advanced Electromagnetic Sensors in Environmental, Industrial and Medical Applications II)
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10 pages, 2852 KiB  
Article
QCL Active Area Modeling with a View to Being Applied to Chemical Substance Detection Systems
by Mariusz Mączka, Grzegorz Hałdaś and Stanisław Pawłowski
Sensors 2023, 23(1), 389; https://doi.org/10.3390/s23010389 - 30 Dec 2022
Cited by 1 | Viewed by 1641
Abstract
Numerical research into the QCL tunability aspects in respect to being applied in chemical substance detection systems is covered in this paper. The QCL tuning opportunities by varying power supply conditions and geometric dimensions of the active area have been considered. Two models [...] Read more.
Numerical research into the QCL tunability aspects in respect to being applied in chemical substance detection systems is covered in this paper. The QCL tuning opportunities by varying power supply conditions and geometric dimensions of the active area have been considered. Two models for superlattice finite (FSML) and infinite (RSM) size were assumed for simulations. The results obtained have been correlated with the absorption map for selected chemical substances in order to identify the potential detection possibilities. Full article
(This article belongs to the Special Issue Advanced Electromagnetic Sensors in Environmental, Industrial and Medical Applications II)
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15 pages, 4421 KiB  
Article
Transient Electromagnetic Processes Analysis in High Voltage Transmission Lines during Two-Phase Short Circuits
by Tomasz Perzyński, Vitaliy Levoniuk and Radosław Figura
Sensors 2023, 23(1), 298; https://doi.org/10.3390/s23010298 - 27 Dec 2022
Cited by 3 | Viewed by 1866
Abstract
The mathematical model of a fragment of a high-voltage electric network is developed in this paper. The network consists of a long power line with distributed parameters and an equivalent three-phase active-inductive load. Neumann and Robin—Poincare boundary conditions were used to identify the [...] Read more.
The mathematical model of a fragment of a high-voltage electric network is developed in this paper. The network consists of a long power line with distributed parameters and an equivalent three-phase active-inductive load. Neumann and Robin—Poincare boundary conditions were used to identify the boundary conditions for the long line equation. The parameter output voltage (voltage at the end of the line) is introduced into the paper for further universal use of the developed line model. On the basis of the developed mathematical model, the program code is written in the algorithmic language Visual Fortran. By means of it, oscillograms of transient electromagnetic processes of voltages and currents in the form of spatial, temporal and temporal-spatial distributions during remote two-phase short circuits in the transmission line of high voltage are obtained. Two transient electromagnetic processes are analyzed in the present work. The first one was analyzed during the switching on of the line to the normal mode of operation with the subsequent transition to the emergency mode. The second one was analyzed during the switching on the line in the mode of a remote two-phase short circuit to the ground. The results of transient electromagnetic process simulation in the form of analyzed figures are shown. All the results presented in this paper were obtained exclusively using numerical methods. Full article
(This article belongs to the Special Issue Advanced Electromagnetic Sensors in Environmental, Industrial and Medical Applications II)
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14 pages, 5576 KiB  
Article
Three Dimensional Membrane Vibration Measurement Using a Two Dimensional Position Sensitive Device
by Rafał Białek and Kamila Białek
Sensors 2023, 23(1), 174; https://doi.org/10.3390/s23010174 - 24 Dec 2022
Cited by 1 | Viewed by 2129
Abstract
This study presents the outcome of research into membrane vibrations in a 3D space performed using a system based on position sensitive device (PSD) sensors. Here, measurements were conducted for harmonic vibrations. The use of such detectors for assessing the movement of objects [...] Read more.
This study presents the outcome of research into membrane vibrations in a 3D space performed using a system based on position sensitive device (PSD) sensors. Here, measurements were conducted for harmonic vibrations. The use of such detectors for assessing the movement of objects within a plane or space requires determining the position of more than one marker. The article reviews two methods for detecting the position of several light spots on a sensor’s photosensitive plane: a marker sequential control method, and a method based on Fast Fourier Transform (FFT) that employs a square wave control signal. The authors present an approach to improving measurement accuracy for both methods. They also discuss the advantages and disadvantages of each. Full article
(This article belongs to the Special Issue Advanced Electromagnetic Sensors in Environmental, Industrial and Medical Applications II)
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18 pages, 7002 KiB  
Article
Development of Electromagnetic Acoustic Transducer System for Coin Classification
by Duy-Vinh Dao, Jen-Tzong Jeng, Van-Dong Doan, Huu-Thang Nguyen and Bo-Yao Liang
Sensors 2022, 22(23), 9055; https://doi.org/10.3390/s22239055 - 22 Nov 2022
Viewed by 2065
Abstract
In this work, a method for identifying counterfeit coins based on an electromagnetic acoustic transducer (EMAT) to detect the difference in the coin’s natural acoustic frequency response is presented. In the experimental system, the acoustic oscillation induced by a pulsed magnetic field is [...] Read more.
In this work, a method for identifying counterfeit coins based on an electromagnetic acoustic transducer (EMAT) to detect the difference in the coin’s natural acoustic frequency response is presented. In the experimental system, the acoustic oscillation induced by a pulsed magnetic field is received by a microphone and recorded by an oscilloscope. The natural acoustic frequency of the coin is resolved by the fast Fourier transform (FFT) method on the computer. It is found that the natural frequencies of the possible counterfeit coins deviate significantly from the standard ranges of 16.9 to 17.4 kHz for the authentic 50 New Taiwan Dollar (NTD) coins. The observed natural frequencies of the coin are consistent with the values predicted by analytical estimation. We also built a prototype EMAT coin classification system to detect the natural acoustic frequency by direct frequency counting using a microcontroller. The prototype system demonstrates that a counterfeit coin can be identified by its natural frequency in less than 30 ms using the EMAT method. The proposed technique can be applied to the vending machine to improve the accuracy in discriminating between authentic and counterfeit coins. Full article
(This article belongs to the Special Issue Advanced Electromagnetic Sensors in Environmental, Industrial and Medical Applications II)
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16 pages, 3296 KiB  
Article
Stress Monitoring Using Wearable Sensors: A Pilot Study and Stress-Predict Dataset
by Talha Iqbal, Andrew J. Simpkin, Davood Roshan, Nicola Glynn, John Killilea, Jane Walsh, Gerard Molloy, Sandra Ganly, Hannah Ryman, Eileen Coen, Adnan Elahi, William Wijns and Atif Shahzad
Sensors 2022, 22(21), 8135; https://doi.org/10.3390/s22218135 - 24 Oct 2022
Cited by 21 | Viewed by 13159
Abstract
With the recent advancements in the field of wearable technologies, the opportunity to monitor stress continuously using different physiological variables has gained significant interest. The early detection of stress can help improve healthcare and minimizes the negative impact of long-term stress. This paper [...] Read more.
With the recent advancements in the field of wearable technologies, the opportunity to monitor stress continuously using different physiological variables has gained significant interest. The early detection of stress can help improve healthcare and minimizes the negative impact of long-term stress. This paper reports outcomes of a pilot study and associated stress-monitoring dataset, named the “Stress-Predict Dataset”, created by collecting physiological signals from healthy subjects using wrist-worn watches with a photoplethysmogram (PPG) sensor. While wearing these watches, 35 healthy volunteers underwent a series of tasks (i.e., Stroop color test, Trier Social Stress Test and Hyperventilation Provocation Test), along with a rest period in-between each task. They also answered questionnaires designed to induce stress levels compatible with daily life. The changes in the blood volume pulse (BVP) and heart rate were recorded by the watch and were labelled as occurring during stress-inducing tasks or a rest period (no stress). Additionally, respiratory rate was estimated using the BVP signal. Statistical models and personalised adaptive reference ranges were used to determine the utility of the proposed stressors and the extracted variables (heart rate and respiratory rate). The analysis showed that the interview session was the most significant stress stimulus, causing a significant variation in heart rate of 27 (77%) participants and respiratory rate of 28 (80%) participants out of 35. The outcomes of this study contribute to the understanding the role of stressors and their association with physiological response and provide a dataset to help develop new wearable solutions for more reliable, valid, and sensitive physio-logical stress monitoring. Full article
(This article belongs to the Special Issue Advanced Electromagnetic Sensors in Environmental, Industrial and Medical Applications II)
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16 pages, 5888 KiB  
Article
The Effects of Sheet Thickness and Excitation Frequency on Hysteresis Loops of Non-Oriented Electrical Steel
by Krzysztof Roman Chwastek
Sensors 2022, 22(20), 7873; https://doi.org/10.3390/s22207873 - 17 Oct 2022
Cited by 6 | Viewed by 2264
Abstract
The paper focuses on modeling the rate dependence of hysteresis loops in conductive magnetic materials. The concept, which was advanced about fifty years ago by Chua, is discussed. It is shown that the viscous-type equation considered by Zirka and co-workers belongs to the [...] Read more.
The paper focuses on modeling the rate dependence of hysteresis loops in conductive magnetic materials. The concept, which was advanced about fifty years ago by Chua, is discussed. It is shown that the viscous-type equation considered by Zirka and co-workers belongs to the class of Chua-type models. The dynamic effects are described with a simple fractional power law. The value of the exponent in the above-mentioned power law may be assessed on the basis of measurements of coercive field strength at different excitation frequencies. To verify the usefulness of the approach, the measurements of hysteresis loops were carried out at several excitation frequencies under standardized conditions for two grades of non-oriented electrical steel. The modeled curves are in a good correspondence with the measured ones. The considered model uses fewer parameters than approaches based on three-term loss separation schemes. Full article
(This article belongs to the Special Issue Advanced Electromagnetic Sensors in Environmental, Industrial and Medical Applications II)
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21 pages, 14442 KiB  
Article
Textronic Glove Translating Polish Sign Language
by Ewa Korzeniewska, Marta Kania and Rafał Zawiślak
Sensors 2022, 22(18), 6788; https://doi.org/10.3390/s22186788 - 8 Sep 2022
Cited by 8 | Viewed by 2675
Abstract
Communication between people is a basic social skill used to exchange information. It is often used for self-express and to meet basic human needs, such as the need for closeness, belonging, and security. This process takes place at different levels, using different means, [...] Read more.
Communication between people is a basic social skill used to exchange information. It is often used for self-express and to meet basic human needs, such as the need for closeness, belonging, and security. This process takes place at different levels, using different means, with specific effects. It generally means a two-way flow of information in the immediate area of contact with another person. When people are communicating using the same language, the flow of information is much easier compared to the situation when two people use two different languages from different language families. The process of social communication with the deaf is difficult as well. It is therefore essential to use modern technologies to facilitate communication with deaf and non-speaking people. This article presents the results of work on a prototype of a glove using textronic elements produced using a physical vacuum deposition process. The signal from the sensors, in the form of resistance changes, is read by the microcontroller, and then it is processed and displayed on a smartphone screen in the form of single letters. During the experiment, 520 letters were signed by each author. The correctness of interpreting the signs was 86.5%. Each letter was recognized within approximately 3 s. One of the main results of the article was also the selection of an appropriate material (Velostat, membrane) that can be used as a sensor for the proposed application solution. The proposed solution can enable communication with the deaf using the finger alphabet, which can be used to spell single words or the most important key words. Full article
(This article belongs to the Special Issue Advanced Electromagnetic Sensors in Environmental, Industrial and Medical Applications II)
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13 pages, 3647 KiB  
Article
Computational Analysis of a Multi-Layered Skin and Cardiac Pacemaker Model Based on Neural Network Approach
by Zuzana Psenakova, Maros Smondrk, Jan Barabas, Mariana Benova, Rafał Brociek, Agata Wajda, Paweł Kowol, Salvatore Coco and Grazia Lo Sciuto
Sensors 2022, 22(17), 6359; https://doi.org/10.3390/s22176359 - 24 Aug 2022
Cited by 2 | Viewed by 2265
Abstract
The presented study discusses the possible disturbing effects of the electromagnetic field of antennas used in mobile phones or WiFi technologies on the pacemaker in the patient’s body. This study aims to obtain information on how the thickness of skin layers (such as [...] Read more.
The presented study discusses the possible disturbing effects of the electromagnetic field of antennas used in mobile phones or WiFi technologies on the pacemaker in the patient’s body. This study aims to obtain information on how the thickness of skin layers (such as the thickness of the hypodermis) can affect the activity of a pacemaker exposed to a high-frequency electromagnetic field. This study describes the computational mathematical analysis and modeling of the heart pacemaker inserted under the skin exposed to various electromagnetic field sources, such as a PIFA antenna and a tuned dipole antenna. The finite integration technique (FIT) for a pacemaker model was implemented within the commercially available CST Microwave simulation software studio. Likewise, the equations that describe the mathematical relationship between the subcutaneous layer thickness and electric field according to different exposures of a tuned dipole and a PIFA antenna are used and applied for training a neural network. The main output of this study is the creation of a mathematical model and a multilayer feedforward neural network, which can show the dependence of the thickness of the hypodermis on the size of the electromagnetic field, from the simulated data from CST Studio. Full article
(This article belongs to the Special Issue Advanced Electromagnetic Sensors in Environmental, Industrial and Medical Applications II)
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17 pages, 29995 KiB  
Article
E-Skin Using Fringing Field Electrical Impedance Tomography with an Ionic Liquid Domain
by Manuchehr Soleimani and Myron Friedrich
Sensors 2022, 22(13), 5040; https://doi.org/10.3390/s22135040 - 4 Jul 2022
Cited by 15 | Viewed by 3559
Abstract
Electrical impedance tomography (EIT) is a promising technique for large area tactile sensing for robotic skin. This study presents a novel EIT-based force and touch sensor that features a latex membrane acting as soft skin and an ionic liquid domain. The sensor works [...] Read more.
Electrical impedance tomography (EIT) is a promising technique for large area tactile sensing for robotic skin. This study presents a novel EIT-based force and touch sensor that features a latex membrane acting as soft skin and an ionic liquid domain. The sensor works based on fringing field EIT where the touch or force leads to a deformation in the latex membrane causing detectable changes in EIT data. This article analyses the performance of this electronic skin in terms of its dynamical behaviour, position accuracy and quantitative force sensing. Investigation into the sensor’s performance showed it to be hypersensitive, in that it can reliably detect forces as small as 64 mN. Furthermore, multi-touch discrimination and annular force sensing is displayed. The hysteresis in force sensing is investigated showing a very negligible hysteresis. This is a direct result of the latex membrane and the ionic liquid-based domain design compared to more traditional fabric-based touch sensors due to the reduction in electromechanical coupling. A novel test is devised that displayed the dynamic performance of the sensor by showing its ability to record a 1 Hz frequency, which was applied to the membrane in a tapping fashion. Overall, the results show a considerable progress in ionic liquid EIT-based sensors. These findings place the EIT-based sensors that comprise a liquid domain, at the forefront of research into tactile robotic skin. Full article
(This article belongs to the Special Issue Advanced Electromagnetic Sensors in Environmental, Industrial and Medical Applications II)
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