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Special Issue "Feature Papers in Physical Sensors Section 2020"

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

Deadline for manuscript submissions: 31 March 2021.

Special Issue Editor

Prof. Dr. Guillermo Villanueva
Website
Guest Editor
École Polytechnique Fédérale de Lausanne (EPFL), Route Cantonale, 1015 Lausanne, Switzerland
Interests: MEMS, NEMS, piezoelectric transduction, resonators, nonlinearity, 2D materials
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to announce that the Physical Sensors Section is now compiling a collection of papers submitted exclusively by Editorial Board Members (EBMs) of our section.

The purpose of this Special Issue is to publish a set of papers that typify the very best insightful and influential original articles or review where our section’s EBMs discuss key topics in the field. We expect these papers to be widely read and highly influential within the field. All papers in this Special Issue will be collected into a printed edition book after the deadline and will be well promoted. 

Taking this opptunately, we would also like to call on more excellent scholars to join the Physical Sensors Section so we can achieve more milestones together.

Dr. Guillermo Villanueva
Editor-in-Chief

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (18 papers)

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Research

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Open AccessArticle
Remote Reflectivity Sensor for Industrial Applications
Sensors 2021, 21(4), 1301; https://doi.org/10.3390/s21041301 - 11 Feb 2021
Abstract
A low-cost optical reflectivity sensor is proposed in this paper, able to detect the presence of objects or surface optical properties variations, at a distance of up to 20 m. A collimated laser beam is pulsed at 10 kHz, and a synchronous digital [...] Read more.
A low-cost optical reflectivity sensor is proposed in this paper, able to detect the presence of objects or surface optical properties variations, at a distance of up to 20 m. A collimated laser beam is pulsed at 10 kHz, and a synchronous digital detector coherently measures the back-diffused light collected through a 1-inch biconvex lens. The sensor is a cost-effective solution for punctual measurement of the surface reflection at different distances. To enhance the interference immunity, an algorithm based on a double-side digital baseline restorer is proposed and implemented to accurately detect the amplitude of the reflected light. As results show, the sensor is robust against ambient light and shows a strong sensitivity on a wide reflection range. The capability of the proposed sensor was evaluated experimentally for object detection and recognition, in addition to dedicated measurement systems, like remote encoders or keyphasors, realized far from the object to be measured. Full article
(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)
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Open AccessArticle
Synchronized Hardware-Registered VIS-NIR Imaging Spectroscopy and 3D Sensing on a Fresco by Botticelli
Sensors 2021, 21(4), 1287; https://doi.org/10.3390/s21041287 - 11 Feb 2021
Abstract
We discuss a synchronised sensing technique for the analysis of painted surfaces of frescos. Specifically, the performance of Visible-Near Infrared (VIS-NIR) Reflectance Imaging Spectroscopy (RIS) synchronized with three-dimensional (3D) acquisition is demonstrated in the study of a detached mural painting by Alessandro Botticelli. [...] Read more.
We discuss a synchronised sensing technique for the analysis of painted surfaces of frescos. Specifically, the performance of Visible-Near Infrared (VIS-NIR) Reflectance Imaging Spectroscopy (RIS) synchronized with three-dimensional (3D) acquisition is demonstrated in the study of a detached mural painting by Alessandro Botticelli. Synchronized sensing generates georeferenced data for simplified data treatment and interpretation. We show how such output data can provide key information to interpret important fresco surface and subsurface features (e.g., painting technique, material composition, pentimenti). Full article
(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)
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Open AccessFeature PaperArticle
Toward the Use of Temporary Tattoo Electrodes for Impedancemetric Respiration Monitoring and Other Electrophysiological Recordings on Skin
Sensors 2021, 21(4), 1197; https://doi.org/10.3390/s21041197 - 08 Feb 2021
Abstract
The development of dry, ultra-conformable and unperceivable temporary tattoo electrodes (TTEs), based on the ink-jet printing of poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) on top of commercially available temporary tattoo paper, has gained increasing attention as a new and promising technology for electrophysiological recordings on [...] Read more.
The development of dry, ultra-conformable and unperceivable temporary tattoo electrodes (TTEs), based on the ink-jet printing of poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) on top of commercially available temporary tattoo paper, has gained increasing attention as a new and promising technology for electrophysiological recordings on skin. In this work, we present a TTEs epidermal sensor for real time monitoring of respiration through transthoracic impedance measurements, exploiting a new design, based on the application of soft screen printed Ag ink and magnetic interlink, that guarantees a repositionable, long-term stable and robust interconnection of TTEs with external “docking” devices. The efficiency of the TTE and the proposed interconnection strategy under stretching (up to 10%) and over time (up to 96 h) has been verified on a dedicated experimental setup and on humans, fulfilling the proposed specific application of transthoracic impedance measurements. The proposed approach makes this technology suitable for large-scale production and suitable not only for the specific use case presented, but also for real time monitoring of different bio-electric signals, as demonstrated through specific proof of concept demonstrators. Full article
(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)
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Open AccessArticle
Acoustic Emission Signal Entropy as a Means to Estimate Loads in Fiber Reinforced Polymer Rods
Sensors 2021, 21(4), 1089; https://doi.org/10.3390/s21041089 - 05 Feb 2021
Abstract
Fibre reinforced polymer (FRP) rods are widely used as corrosion-resistant reinforcing in civil structures. However, developing a method to determine the loads on in-service FRP rods remains a challenge. In this study, the entropy of acoustic emission (AE) emanating from FRP rods is [...] Read more.
Fibre reinforced polymer (FRP) rods are widely used as corrosion-resistant reinforcing in civil structures. However, developing a method to determine the loads on in-service FRP rods remains a challenge. In this study, the entropy of acoustic emission (AE) emanating from FRP rods is used to estimate the applied loads. As loads increased, the fraction of AE hits with higher entropy also increased. High entropy AE hits are defined using the one-sided Chebyshev’s inequality with parameter k = 2 where the histogram of AE entropy up to 10–15% of ultimate load was used as a baseline. According to the one-sided Chebyshev’s inequality, when more than 20% (k = 2) of AE hits that fall further than two standard deviations away from the mean are classified as high entropy events, a new distribution of high entropy AE hits is assumed to exist. We have found that the fraction of high AE hits. In glass FRP and carbon FRP rods, a high entropy AE hit fraction of 20% was exceeded at approximately 40% and 50% of the ultimate load, respectively. This work demonstrates that monitoring high entropy AE hits may provide a useful means to estimate the loads on FRP rods. Full article
(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)
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Open AccessArticle
A Lightweight Exoskeleton-Based Portable Gait Data Collection System
Sensors 2021, 21(3), 781; https://doi.org/10.3390/s21030781 - 24 Jan 2021
Abstract
For the controller of wearable lower-limb assistive devices, quantitative understanding of human locomotion serves as the basis for human motion intent recognition and joint-level motion control. Traditionally, the required gait data are obtained in gait research laboratories, utilizing marker-based optical motion capture systems. [...] Read more.
For the controller of wearable lower-limb assistive devices, quantitative understanding of human locomotion serves as the basis for human motion intent recognition and joint-level motion control. Traditionally, the required gait data are obtained in gait research laboratories, utilizing marker-based optical motion capture systems. Despite the high accuracy of measurement, marker-based systems are largely limited to laboratory environments, making it nearly impossible to collect the desired gait data in real-world daily-living scenarios. To address this problem, the authors propose a novel exoskeleton-based gait data collection system, which provides the capability of conducting independent measurement of lower limb movement without the need for stationary instrumentation. The basis of the system is a lightweight exoskeleton with articulated knee and ankle joints. To minimize the interference to a wearer’s natural lower-limb movement, a unique two-degrees-of-freedom joint design is incorporated, integrating a primary degree of freedom for joint motion measurement with a passive degree of freedom to allow natural joint movement and improve the comfort of use. In addition to the joint-embedded goniometers, the exoskeleton also features multiple positions for the mounting of inertia measurement units (IMUs) as well as foot-plate-embedded force sensing resistors to measure the foot plantar pressure. All sensor signals are routed to a microcontroller for data logging and storage. To validate the exoskeleton-provided joint angle measurement, a comparison study on three healthy participants was conducted, which involves locomotion experiments in various modes, including overground walking, treadmill walking, and sit-to-stand and stand-to-sit transitions. Joint angle trajectories measured with an eight-camera motion capture system served as the benchmark for comparison. Experimental results indicate that the exoskeleton-measured joint angle trajectories closely match those obtained through the optical motion capture system in all modes of locomotion (correlation coefficients of 0.97 and 0.96 for knee and ankle measurements, respectively), clearly demonstrating the accuracy and reliability of the proposed gait measurement system. Full article
(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)
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Open AccessArticle
Inferring the Driver’s Lane Change Intention through LiDAR-Based Environment Analysis Using Convolutional Neural Networks
Sensors 2021, 21(2), 475; https://doi.org/10.3390/s21020475 - 11 Jan 2021
Abstract
Most of the tactic manoeuvres during driving require a certain understanding of the surrounding environment from which to devise our future behaviour. In this paper, a Convolutional Neural Network (CNN) approach is used to model the lane change behaviour to identify when a [...] Read more.
Most of the tactic manoeuvres during driving require a certain understanding of the surrounding environment from which to devise our future behaviour. In this paper, a Convolutional Neural Network (CNN) approach is used to model the lane change behaviour to identify when a driver is going to perform this manoeuvre. To that end, a slightly modified CNN architecture adapted to both spatial (i.e., surrounding environment) and non-spatial (i.e., rest of variables such as relative speed to the front vehicle) input variables. Anticipating a driver’s lane change intention means it is possible to use this information as a new source of data in wide range of different scenarios. One example of such scenarios might be the decision making process support for human drivers through Advanced Driver Assistance Systems (ADAS) fed with the data of the surrounding cars in an inter-vehicular network. Another example might even be its use in autonomous vehicles by using the data of a specific driver profile to make automated driving more human-like. Several CNN architectures have been tested on a simulation environment to assess their performance. Results show that the selected architecture provides a higher degree of accuracy than random guessing (i.e., assigning a class randomly for each observation in the data set), and it can capture subtle differences in behaviour between different driving profiles. Full article
(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)
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Open AccessArticle
In-Situ Estimation of Soil Water Retention Curve in Silt Loam and Loamy Sand Soils at Different Soil Depths
Sensors 2021, 21(2), 447; https://doi.org/10.3390/s21020447 - 10 Jan 2021
Abstract
The soil water retention curve (SWRC) shows the relationship between soil water (θ) and water potential (ψ) and provides fundamental information for quantifying and modeling soil water entry, storage, flow, and groundwater recharge processes. While traditionally it is measured in a laboratory through [...] Read more.
The soil water retention curve (SWRC) shows the relationship between soil water (θ) and water potential (ψ) and provides fundamental information for quantifying and modeling soil water entry, storage, flow, and groundwater recharge processes. While traditionally it is measured in a laboratory through cumbersome and time-intensive methods, soil sensors measuring in-situ θ and ψ show strong potential to estimate in-situ SWRC. The objective of this study was to estimate in-situ SWRC at different depths under two different soil types by integrating measured θ and ψ using two commercial sensors: time-domain reflectometer (TDR) and dielectric field water potential (e.g., MPS-6) principles. Parametric models were used to quantify θ—ψ relationships at various depths and were compared to laboratory-measured SWRC. The results of the study show that combining TDR and MPS-6 sensors can be used to estimate plant-available water and SWRC, with a mean difference of −0.03 to 0.23 m3m−3 between the modeled data and laboratory data, which could be caused by the sensors’ lack of site-specific calibration or possible air entrapment of field soil. However, consistent trends (with magnitude differences) indicated the potential to use these sensors in estimating in-situ and dynamic SWRC at depths and provided a way forward in overcoming resource-intensive laboratory measurements. Full article
(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)
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Open AccessArticle
Twelve-Year Analysis of NO2 Concentration Measurements at Belisario Station (Quito, Ecuador) Using Statistical Inference Techniques
Sensors 2020, 20(20), 5831; https://doi.org/10.3390/s20205831 - 15 Oct 2020
Cited by 1
Abstract
In this paper, a robust analysis of nitrogen dioxide (NO2) concentration measurements taken at Belisario station (Quito, Ecuador) was performed. The data used for the analysis constitute a set of measurements taken from 1 January 2008 to 31 December 2019. Furthermore, [...] Read more.
In this paper, a robust analysis of nitrogen dioxide (NO2) concentration measurements taken at Belisario station (Quito, Ecuador) was performed. The data used for the analysis constitute a set of measurements taken from 1 January 2008 to 31 December 2019. Furthermore, the analysis was carried out in a robust way, defining variables that represent years, months, days and hours, and classifying these variables based on estimates of the central tendency and dispersion of the data. The estimators used here were classic, nonparametric, based on a bootstrap method, and robust. Additionally, confidence intervals based on these estimators were built, and these intervals were used to categorize the variables under study. The results of this research showed that the NO2 concentration at Belisario station is not harmful to humans. Moreover, it was shown that this concentration tends to be stable across the years, changes slightly during the days of the week, and varies greatly when analyzed by months and hours of the day. Here, the precision provided by both nonparametric and robust statistical methods served to comprehensively proof the aforementioned. Finally, it can be concluded that the city of Quito is progressing on the right path in terms of improving air quality, because it has been shown that there is a decreasing tendency in the NO2 concentration across the years. In addition, according to the Quito Air Quality Index, most of the observations are in either the desirable level or acceptable level of air pollution, and the number of observations that are in the desirable level of air pollution increases across the years. Full article
(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)
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Open AccessArticle
Deep Physiological Model for Blood Glucose Prediction in T1DM Patients
Sensors 2020, 20(14), 3896; https://doi.org/10.3390/s20143896 - 13 Jul 2020
Abstract
Accurate estimations for the near future levels of blood glucose are crucial for Type 1 Diabetes Mellitus (T1DM) patients in order to be able to react on time and avoid hypo and hyper-glycemic episodes. Accurate predictions for blood glucose are the base for [...] Read more.
Accurate estimations for the near future levels of blood glucose are crucial for Type 1 Diabetes Mellitus (T1DM) patients in order to be able to react on time and avoid hypo and hyper-glycemic episodes. Accurate predictions for blood glucose are the base for control algorithms in glucose regulating systems such as the artificial pancreas. Numerous research studies have already been conducted in order to provide predictions for blood glucose levels with particularities in the input signals and underlying models used. These models can be categorized into two major families: those based on tuning glucose physiological-metabolic models and those based on learning glucose evolution patterns based on machine learning techniques. This paper reviews the state of the art in blood glucose predictions for T1DM patients and proposes, implements, validates and compares a new hybrid model that decomposes a deep machine learning model in order to mimic the metabolic behavior of physiological blood glucose methods. The differential equations for carbohydrate and insulin absorption in physiological models are modeled using a Recurrent Neural Network (RNN) implemented using Long Short-Term Memory (LSTM) cells. The results show Root Mean Square Error (RMSE) values under 5 mg/dL for simulated patients and under 10 mg/dL for real patients. Full article
(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)
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Open AccessArticle
Technique and Circuit for Contactless Readout of Piezoelectric MEMS Resonator Sensors
Sensors 2020, 20(12), 3483; https://doi.org/10.3390/s20123483 - 19 Jun 2020
Cited by 1
Abstract
A technique and electronic circuit for contactless electromagnetic interrogation of piezoelectric micro-electromechanical system (MEMS) resonator sensors are proposed. The adopted resonator is an aluminum-nitride (AlN) thin-film piezoelectric-on-silicon (TPoS) disk vibrating in radial contour mode at about 6.3 MHz. The MEMS resonator is operated [...] Read more.
A technique and electronic circuit for contactless electromagnetic interrogation of piezoelectric micro-electromechanical system (MEMS) resonator sensors are proposed. The adopted resonator is an aluminum-nitride (AlN) thin-film piezoelectric-on-silicon (TPoS) disk vibrating in radial contour mode at about 6.3 MHz. The MEMS resonator is operated in one-port configuration and it is connected to a spiral coil, forming the sensor unit. A proximate electronic interrogation unit is electromagnetically coupled through a readout coil to the sensor unit. The proposed technique exploits interleaved excitation and detection phases of the MEMS resonator. A tailored electronic circuit manages the periodic switching between the excitation phase, where it generates the excitation signal driving the readout coil, and the detection phase, where it senses the transient decaying response of the resonator by measuring through a high-impedance amplifier the voltage induced back across the readout coil. This approach advantageously ensures that the readout frequency of the MEMS resonator is first order independent of the interrogation distance between the readout and sensor coils. The reported experimental results show successful contactless readout of the MEMS resonator independently from the interrogation distance over a range of 12 mm, and the application as a resonant sensor for ambient temperature and as a resonant acoustic-load sensor to detect and track the deposition and evaporation processes of water microdroplets on the MEMS resonator surface. Full article
(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)
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Open AccessArticle
Polymer Optical Fiber-Based Integrated Instrumentation in a Robot-Assisted Rehabilitation Smart Environment: A Proof of Concept
Sensors 2020, 20(11), 3199; https://doi.org/10.3390/s20113199 - 04 Jun 2020
Cited by 1
Abstract
Advances in robotic systems for rehabilitation purposes have led to the development of specialized robot-assisted rehabilitation clinics. In addition, advantageous features of polymer optical fiber (POF) sensors such as light weight, multiplexing capabilities, electromagnetic field immunity and flexibility have resulted in the widespread [...] Read more.
Advances in robotic systems for rehabilitation purposes have led to the development of specialized robot-assisted rehabilitation clinics. In addition, advantageous features of polymer optical fiber (POF) sensors such as light weight, multiplexing capabilities, electromagnetic field immunity and flexibility have resulted in the widespread use of POF sensors in many areas. Considering this background, this paper presents an integrated POF intensity variation-based sensor system for the instrumentation of different devices. We consider different scenarios for physical rehabilitation, resembling a clinic for robot-assisted rehabilitation. Thus, a multiplexing technique for POF intensity variation-based sensors was applied in which an orthosis for flexion/extension movement, a modular exoskeleton for gait assistance and a treadmill were instrumented with POF angle and force sensors, where all the sensors were integrated in the same POF system. In addition, wearable sensors for gait analysis and physiological parameter monitoring were also proposed and applied in gait exercises. The results show the feasibility of the sensors and methods proposed, where, after the characterization of each sensor, the system was implemented with three volunteers: one for the orthosis on the flexion/extension movements, one for the exoskeleton for gait assistance and the other for the free gait analysis using the proposed wearable POF sensors. To the authors’ best knowledge, this is the first time that optical fiber sensors have been used as a multiplexed and integrated solution for the simultaneous assessment of different robotic devices and rehabilitation protocols, where such an approach results in a compact, fully integrated and low-cost system, which can be readily employed in any clinical environment. Full article
(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)
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Review

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Open AccessReview
Planar Phase-Variation Microwave Sensors for Material Characterization: A Review and Comparison of Various Approaches
Sensors 2021, 21(4), 1542; https://doi.org/10.3390/s21041542 (registering DOI) - 23 Feb 2021
Abstract
Planar phase-variation microwave sensors have attracted increasing interest in recent years since they combine the advantages of planar technology (including low cost, low profile, and sensor integration with the associated circuitry for post-processing and communication purposes, among others) and the possibility of operation [...] Read more.
Planar phase-variation microwave sensors have attracted increasing interest in recent years since they combine the advantages of planar technology (including low cost, low profile, and sensor integration with the associated circuitry for post-processing and communication purposes, among others) and the possibility of operation at a single frequency (thereby reducing the costs of the associated electronics). This paper reviews and compares three different strategies for sensitivity improvement in such phase-variation sensors (devoted to material characterization). The considered approaches include line elongation (through meandering), dispersion engineering (by considering slow-wave artificial transmission lines), and reflective-mode sensors based on step-impedance open-ended lines. It is shown that unprecedented sensitivities compatible with small sensing regions are achievable with the latter approach. Full article
(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)
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Open AccessReview
Sensors and Measurements for Unmanned Systems: An Overview
Sensors 2021, 21(4), 1518; https://doi.org/10.3390/s21041518 - 22 Feb 2021
Abstract
The advance of technology has enabled the development of unmanned systems/vehicles used in the air, on the ground or on/in the water. The application range for these systems is continuously increasing, and unmanned platforms continue to be the subject of numerous studies and [...] Read more.
The advance of technology has enabled the development of unmanned systems/vehicles used in the air, on the ground or on/in the water. The application range for these systems is continuously increasing, and unmanned platforms continue to be the subject of numerous studies and research contributions. This paper deals with the role of sensors and measurements in ensuring that unmanned systems work properly, meet the requirements of the target application, provide and increase their navigation capabilities, and suitably monitor and gain information on several physical quantities in the environment around them. Unmanned system types and the critical environmental factors affecting their performance are discussed. The measurements that these kinds of vehicles can carry out are presented and discussed, while also describing the most frequently used on-board sensor technologies, as well as their advantages and limitations. The paper provides some examples of sensor specifications related to some current applications, as well as describing the recent research contributions in the field. Full article
(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)
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Open AccessReview
Magnetic Microwires with Unique Combination of Magnetic Properties Suitable for Various Magnetic Sensor Applications
Sensors 2020, 20(24), 7203; https://doi.org/10.3390/s20247203 - 16 Dec 2020
Abstract
There is a pressing demand to improve the performance of cost-effective soft magnetic materials for use in high performance sensors and devices. Giant Magneto-impedance effect (GMI), or fast single domain wall (DW) propagation can be observed in properly processed magnetic microwires. In this [...] Read more.
There is a pressing demand to improve the performance of cost-effective soft magnetic materials for use in high performance sensors and devices. Giant Magneto-impedance effect (GMI), or fast single domain wall (DW) propagation can be observed in properly processed magnetic microwires. In this paper we have identified the routes to obtain microwires with unique combination of magnetic properties allowing observation of fast and single DW propagation and GMI effect in the same microwire. By modifying the annealing conditions, we have found the appropriate regimes allowing achievement of the highest GMI ratio and the fastest DW dynamics. The observed experimental results are discussed considering the radial distribution of magnetic anisotropy and the correlation of GMI effect, and DW dynamics with bulk and surface magnetization processes. Studies of both Fe- and Co-rich microwires, using the magneto-optical Kerr effect, MOKE, provide information on the magnetic structure in the outer shell of microwires. We have demonstrated the existence of the spiral helical structure in both studied microwires. At the same time, torsion mechanical stresses induce helical bistability in the same microwires, which allow us to consider these microwires as materials suitable for sensors based on the large Barkhausen jump. Full article
(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)
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Open AccessReview
Wavefront Shaping Concepts for Application in Optical Coherence Tomography—A Review
Sensors 2020, 20(24), 7044; https://doi.org/10.3390/s20247044 - 09 Dec 2020
Abstract
Optical coherence tomography (OCT) enables three-dimensional imaging with resolution on the micrometer scale. The technique relies on the time-of-flight gated detection of light scattered from a sample and has received enormous interest in applications as versatile as non-destructive testing, metrology and non-invasive medical [...] Read more.
Optical coherence tomography (OCT) enables three-dimensional imaging with resolution on the micrometer scale. The technique relies on the time-of-flight gated detection of light scattered from a sample and has received enormous interest in applications as versatile as non-destructive testing, metrology and non-invasive medical diagnostics. However, in strongly scattering media such as biological tissue, the penetration depth and imaging resolution are limited. Combining OCT imaging with wavefront shaping approaches significantly leverages the capabilities of the technique by controlling the scattered light field through manipulation of the field incident on the sample. This article reviews the main concepts developed so far in the field and discusses the latest results achieved with a focus on signal enhancement and imaging. Full article
(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)
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Open AccessReview
Fundamental Concepts and Evolution of Wi-Fi User Localization: An Overview Based on Different Case Studies
Sensors 2020, 20(18), 5121; https://doi.org/10.3390/s20185121 - 08 Sep 2020
Cited by 1
Abstract
Indoor positioning poses a number of challenges, especially in large and complex buildings. Several effects, such as signal attenuation, signal fluctuations, interference, and multipath play a decisive role in signal propagation. The severity of each challenge depends on the method and technology adopted [...] Read more.
Indoor positioning poses a number of challenges, especially in large and complex buildings. Several effects, such as signal attenuation, signal fluctuations, interference, and multipath play a decisive role in signal propagation. The severity of each challenge depends on the method and technology adopted to perform user localization. Wi-Fi is a popular method because of its ubiquity with already available public and private infrastructure in many environments and the ability for mobile clients, such as smartphones, to receive these signals. In this contribution, the fundamental concepts and basics and the evolution of Wi-Fi as the most widely used indoor positioning technology are reviewed and demonstrated using four different conducted case studies. Starting from an analysis of the properties of Wi-Fi signals and their propagation, suitable techniques are identified. The mathematical models of location fingerprinting and lateration are consolidated and assessed as well as new technology directions and developments highlighted. Results of the case studies demonstrate the capability of Wi-Fi for continuous user localization also in dynamic environments and kinematic mode where the user walks with a usual step speed. However, to achieve acceptable localization accuracy, calibration of the devices is required to mitigate the variance problems due to the device heterogeneity. Full article
(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)
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Open AccessReview
Micromachined Accelerometers with Sub-µg/√Hz Noise Floor: A Review
Sensors 2020, 20(14), 4054; https://doi.org/10.3390/s20144054 - 21 Jul 2020
Cited by 5
Abstract
This paper reviews the research and development of micromachined accelerometers with a noise floor lower than 1 µg/√Hz. Firstly, the basic working principle of micromachined accelerometers is introduced. Then, different methods of reducing the noise floor of micromachined accelerometers are analyzed. Different types [...] Read more.
This paper reviews the research and development of micromachined accelerometers with a noise floor lower than 1 µg/√Hz. Firstly, the basic working principle of micromachined accelerometers is introduced. Then, different methods of reducing the noise floor of micromachined accelerometers are analyzed. Different types of micromachined accelerometers with a noise floor below 1 µg/√Hz are discussed. Such sensors can mainly be categorized into: (i) micromachined accelerometers with a low spring constant; (ii) with a large proof mass; (iii) with a high quality factor; (iv) with a low noise interface circuit; (v) with sensing schemes leading to a high scale factor. Finally, the characteristics of various micromachined accelerometers and their trends are discussed and investigated. Full article
(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)
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Other

Jump to: Research, Review

Open AccessPerspective
Noise as Diagnostic Tool for Quality and Reliability of MEMS
Sensors 2021, 21(4), 1510; https://doi.org/10.3390/s21041510 - 22 Feb 2021
Abstract
This perspective explores future research approaches on the use of noise characteristics of microelectromechanical systems (MEMS) devices as a diagnostic tool to assess their quality and reliability. Such a technique has been applied to electronic devices. In comparison to these, however, MEMS have [...] Read more.
This perspective explores future research approaches on the use of noise characteristics of microelectromechanical systems (MEMS) devices as a diagnostic tool to assess their quality and reliability. Such a technique has been applied to electronic devices. In comparison to these, however, MEMS have much more diverse materials, structures, and transduction mechanisms. Correspondingly, we must deal with various types of noise sources and a means to separate their contributions. In this paper, we first provide an overview of reliability and noise in MEMS and then suggest a framework to link noise data of specific devices to their quality or reliability. After this, we analyze 13 classes of MEMS and recommend four that are most amenable to this approach. Finally, we propose a noise measurement system to separate the contribution of electrical and mechanical noise sources. Through this perspective, our hope is for current and future designers of MEMS to see the potential benefits of noise in their devices. Full article
(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

1. Polymer Optical Fiber-based Integrated Instrumentation of a Robotic-Assisted Rehabilitation Smart Environment: a Proof of Concept
Carlos Marques

2. Technique and Circuit for Contactless Readout of Piezoelectric MEMS Resonator Sensors
Vittorio Ferrari

3. Planar Microwave Phase-variation Sensors for Material Characterization: A Review and Comparison of Various Approaches
Ferran Martín

4. 3D volumetric mosaic process for photoacoustic microscopy using SURF
Changho Lee

5. Electronic surveillance and security applications of magnetic
microwires
Valentina Zhukova

6. Synchronised Sensorial Approach for the Analysis of Paintings
Luca Pezzati  

7. Machine Learning Approach for Agricultural Sensing in Land Classification using Synthetic Aperture Radar Measurements
Aimé Lay-Ekuakille

8. Temperature control of laser treatment during shellac coating removal from wall paintings
Luca Pezzati  

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