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A special issue of Sensors (ISSN 1424-8220).

Deadline for manuscript submissions: closed (31 March 2021) | Viewed by 60525

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Dr. Debbie G. Senesky

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Aeronautics and Astronautics Department, Stanford University, Durand Building #254, 496 Lomita Mall, Stanford, CA 94305, USA
Interests: harsh environment sensors; wide bandgap semiconductors; compound semiconductors; high-temperature instrumentation; radiation hardened semiconductors; semiconductor sensors; optical sensors; chemical sensors; micromechanical resonators; energy harvesters; piezoelectricity; microfabrication; nanotechnology
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Prof. Dr. Nicole Jaffrezic-Renault

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Institute of Analytical Sciences, UMR CNRS 5280, Department LSA, 5 Rue de La Doua, 69100 Villeurbanne, France
Interests: biosensors; impedance; immunosensors; conductometric sensors; enzymatic sensors; affinity sensors
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

2020 is Sensors’ 20th anniversary. Since its launch in 2001, Sensors has received important support and excellent contributions from women scientists. They have served as our Editorial Board members, Guest Editors, authors, reviewers.

To celebrate and highlight the achievements of women in the sensors research area, this Special Issue, entitled "Women in Sensors", will present the sensors-related work from leading women scientists. We also hope that this Special Issue will further encourage and promote the scientific contributions of women researchers in this field.

A “Women in Sensors Award” will be launched and granted to the best paper published in this Special Issue. Each award nominee will be assessed on her paper’s originality, quality, and contribution to the field by the Evaluation Committee. The winner will receive a certificate, an award of 1000 CHF, and an opportunity to publish her next submission in Sensors free of charge.

Prof. Dr. Debbie G. Senesky
Prof. Dr. Nicole Jaffrezic-Renault
Guest Editors

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 submissions that pass pre-check are 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 2600 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 (14 papers)

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Research

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16 pages, 23388 KiB

Open AccessArticle

Experiencing the Untouchable: A Method for Scientific Exploration and Haptic Fruition of Artworks Microsurface Based on Optical Scanning Profilometry

by Sara Mazzocato and Claudia Daffara

Sensors 2021, 21(13), 4311; https://0-doi-org.brum.beds.ac.uk/10.3390/s21134311 - 24 Jun 2021

Cited by 8 | Viewed by 2540

Abstract

The experience of an object derives not only from the sight but also from the touch: a tactile exploration can reveal the smallest information trapped within the surface up to our tactile detective threshold. Starting from the importance of this observation in the case of works of art, this research demonstrates the use of conoscopic holography sensors for high-quality acquisition of the surface of artworks (up to the micro-scale) suitable also to 3D printing. The purpose is twofold, allowing for the tactile use of the artwork, which is otherwise impossible, for visually impaired people and for new use in regard to scientific information purposes. In detail, the workflow to obtain a 3D printed replica of multiscale and polychrome artworks suitable for the haptic fruition is validated, but the potential of the tool as an innovative resource for scientific visualization of the microsurface of the artwork for conservation issues is also demonstrated. The validation was performed on notable Italian masterpieces, such as Donatello’s “Death Cristh” bronze relief in Padua and the Tintoretto painting “St. Martial in Glory with the Saints Peter and Paul” in Venice. Full article

(This article belongs to the Special Issue Women in Sensors)

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12 pages, 24181 KiB

Open AccessArticle

Machine Learning Based Object Classification and Identification Scheme Using an Embedded Millimeter-Wave Radar Sensor

by Homa Arab, Iman Ghaffari, Lydia Chioukh, Serioja Tatu and Steven Dufour

Sensors 2021, 21(13), 4291; https://0-doi-org.brum.beds.ac.uk/10.3390/s21134291 - 23 Jun 2021

Cited by 10 | Viewed by 3160

Abstract

A target’s movements and radar cross sections are the key parameters to consider when designing a radar sensor for a given application. This paper shows the feasibility and effectiveness of using 24 GHz radar built-in low-noise microwave amplifiers for detecting an object. For this purpose a supervised machine learning model (SVM) is trained using the recorded data to classify the targets based on their cross sections into four categories. The trained classifiers were used to classify the objects with varying distances from the receiver. The SVM classification is also compared with three methods based on binary classification: a one-against-all classification, a one-against-one classification, and a directed acyclic graph SVM. The level of accuracy is approximately 96.6%, and an F1-score of 96.5% is achieved using the one-against-one SVM method with an RFB kernel. The proposed contactless radar in combination with an SVM algorithm can be used to detect and categorize a target in real time without a signal processing toolbox. Full article

(This article belongs to the Special Issue Women in Sensors)

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22 pages, 1665 KiB

Open AccessArticle

Inertial Sensor-Based Step Length Estimation Model by Means of Principal Component Analysis

by Melanija Vezočnik, Roman Kamnik and Matjaz B. Juric

Sensors 2021, 21(10), 3527; https://0-doi-org.brum.beds.ac.uk/10.3390/s21103527 - 19 May 2021

Cited by 9 | Viewed by 2887

Abstract

Inertial sensor-based step length estimation has become increasingly important with the emergence of pedestrian-dead-reckoning-based (PDR-based) indoor positioning. So far, many refined step length estimation models have been proposed to overcome the inaccuracy in estimating distance walked. Both the kinematics associated with the human body during walking and actual step lengths are rarely used in their derivation. Our paper presents a new step length estimation model that utilizes acceleration magnitude. To the best of our knowledge, we are the first to employ principal component analysis (PCA) to characterize the experimental data for the derivation of the model. These data were collected from anatomical landmarks on the human body during walking using a highly accurate optical measurement system. We evaluated the performance of the proposed model for four typical smartphone positions for long-term human walking and obtained promising results: the proposed model outperformed all acceleration-based models selected for the comparison producing an overall mean absolute stride length estimation error of 6.44 cm. The proposed model was also least affected by walking speed and smartphone position among acceleration-based models and is unaffected by smartphone orientation. Therefore, the proposed model can be used in the PDR-based indoor positioning with an important advantage that no special care regarding orientation is needed in attaching the smartphone to a particular body segment. All the sensory data acquired by smartphones that we utilized for evaluation are publicly available and include more than 10 h of walking measurements. Full article

(This article belongs to the Special Issue Women in Sensors)

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12 pages, 1262 KiB

Open AccessArticle

Digital Biomarker Representing Frailty Phenotypes: The Use of Machine Learning and Sensor-Based Sit-to-Stand Test

by Catherine Park, Ramkinker Mishra, Amir Sharafkhaneh, Mon S. Bryant, Christina Nguyen, Ilse Torres, Aanand D. Naik and Bijan Najafi

Sensors 2021, 21(9), 3258; https://0-doi-org.brum.beds.ac.uk/10.3390/s21093258 - 08 May 2021

Cited by 17 | Viewed by 3014

Abstract

Since conventional screening tools for assessing frailty phenotypes are resource intensive and unsuitable for routine application, efforts are underway to simplify and shorten the frailty screening protocol by using sensor-based technologies. This study explores whether machine learning combined with frailty modeling could determine the least sensor-derived features required to identify physical frailty and three key frailty phenotypes (slowness, weakness, and exhaustion). Older participants (n = 102, age = 76.54 ± 7.72 years) were fitted with five wearable sensors and completed a five times sit-to-stand test. Seventeen sensor-derived features were extracted and used for optimal feature selection based on a machine learning technique combined with frailty modeling. Mean of hip angular velocity range (indicator of slowness), mean of vertical power range (indicator of weakness), and coefficient of variation of vertical power range (indicator of exhaustion) were selected as the optimal features. A frailty model with the three optimal features had an area under the curve of 85.20%, a sensitivity of 82.70%, and a specificity of 71.09%. This study suggests that the three sensor-derived features could be used as digital biomarkers of physical frailty and phenotypes of slowness, weakness, and exhaustion. Our findings could facilitate future design of low-cost sensor-based technologies for remote physical frailty assessments via telemedicine. Full article

(This article belongs to the Special Issue Women in Sensors)

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23 pages, 2103 KiB

Open AccessArticle

Abnormal Gait Detection Using Wearable Hall-Effect Sensors

by Courtney Chheng and Denise Wilson

Sensors 2021, 21(4), 1206; https://0-doi-org.brum.beds.ac.uk/10.3390/s21041206 - 09 Feb 2021

Cited by 5 | Viewed by 5487

Abstract

Abnormalities and irregularities in walking (gait) are predictors and indicators of both disease and injury. Gait has traditionally been monitored and analyzed in clinical settings using complex video (camera-based) systems, pressure mats, or a combination thereof. Wearable gait sensors offer the opportunity to collect data in natural settings and to complement data collected in clinical settings, thereby offering the potential to improve quality of care and diagnosis for those whose gait varies from healthy patterns of movement. This paper presents a gait monitoring system designed to be worn on the inner knee or upper thigh. It consists of low-power Hall-effect sensors positioned on one leg and a compact magnet positioned on the opposite leg. Wireless data collected from the sensor system were used to analyze stride width, stride width variability, cadence, and cadence variability for four different individuals engaged in normal gait, two types of abnormal gait, and two types of irregular gait. Using leg gap variability as a proxy for stride width variability, 81% of abnormal or irregular strides were accurately identified as different from normal stride. Cadence was surprisingly 100% accurate in identifying strides which strayed from normal, but variability in cadence provided no useful information. This highly sensitive, non-contact Hall-effect sensing method for gait monitoring offers the possibility for detecting visually imperceptible gait variability in natural settings. These nuanced changes in gait are valuable for predicting early stages of disease and also for indicating progress in recovering from injury. Full article

(This article belongs to the Special Issue Women in Sensors)

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13 pages, 3565 KiB

Open AccessArticle

Silver Nanowires as Electron Transfer Mediators in Electrochemical Catechol Biosensors

by Coral Salvo-Comino, Fernando Martin-Pedrosa, Cristina Garcia-Cabezon and Maria Luz Rodriguez-Mendez

Sensors 2021, 21(3), 899; https://0-doi-org.brum.beds.ac.uk/10.3390/s21030899 - 29 Jan 2021

Cited by 27 | Viewed by 2706

Abstract

The integration of nanomaterials as electron mediators in electrochemical biosensors is taking on an essential role. Due to their high surface-to-volume ratio and high conductivity, metallic nanowires are an interesting option. In this paper, silver nanowires (AgNWs) were exploited to design a novel catechol electrochemical biosensor, and the benefits of increasing the aspect ratio of the electron mediator (nanowires vs. nanoparticles) were analyzed. Atomic force microscopy (AFM) studies have shown a homogeneous distribution of the enzyme along the silver nanowires, maximizing the contact surface. The large contact area promotes electron transfer between the enzyme and the electrode surface, resulting in a Limit of Detection (LOD) of 2.7 × 10⁻⁶ M for tyrosinase immobilized onto AgNWs (AgNWs-Tyr), which is one order of magnitude lower than the LOD of 3.2 × 10⁻⁵ M) obtained using tyrosinase immobilized onto silver nanoparticles (AgNPs-Tyr). The calculated K_M constant was 122 mM. The simultaneous use of electrochemistry and AFM has demonstrated a limited electrochemical fouling that facilitates stable and reproducible detection. Finally, the biosensor showed excellent anti-interference characteristics toward the main phenols present in wines including vanillin, pyrogallol, quercetin and catechin. The biosensor was able to successfully detect the presence of catechol in real wine samples. These results make AgNWs promising elements in nanowired biosensors for the sensitive, stable and rapid voltammetric detection of phenols in real applications. Full article

(This article belongs to the Special Issue Women in Sensors)

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21 pages, 4244 KiB

Open AccessArticle

Quantitative Comparison of UAS-Borne LiDAR Systems for High-Resolution Forested Wetland Mapping

by Narcisa Gabriela Pricope, Joanne Nancie Halls, Kerry Lynn Mapes, Joseph Britton Baxley and James JyunYueh Wu

Sensors 2020, 20(16), 4453; https://0-doi-org.brum.beds.ac.uk/10.3390/s20164453 - 10 Aug 2020

Cited by 12 | Viewed by 3135

Abstract

Wetlands provide critical ecosystem services across a range of environmental gradients and are at heightened risk of degradation from anthropogenic pressures and continued development, especially in coastal regions. There is a growing need for high-resolution (spatially and temporally) habitat identification and precise delineation of wetlands across a variety of stakeholder groups, including wetlands loss mitigation programs. Traditional wetland delineations are costly, time-intensive and can physically degrade the systems that are being surveyed, while aerial surveys are relatively fast and relatively unobtrusive. To assess the efficacy and feasibility of using two variable-cost LiDAR sensors mounted on a commercial hexacopter unmanned aerial system (UAS) in deriving high resolution topography, we conducted nearly concomitant flights over a site located in the Atlantic Coastal plain that contains a mix of palustrine forested wetlands, upland coniferous forest, upland grass and bare ground/dirt roads. We compared point clouds and derived topographic metrics acquired using the Quanergy M8 and the Velodyne HDL-32E LiDAR sensors with airborne LiDAR and results showed that the less expensive and lighter payload sensor outperforms the more expensive one in deriving high resolution, high accuracy ground elevation measurements under a range of canopy cover densities and for metrics of point cloud density and digital terrain computed both globally and locally using variable size tessellations. The mean point cloud density was not significantly different between wetland and non-wetland areas, but the two sensors were significantly different by wetland/non-wetland type. Ultra-high-resolution LiDAR-derived topography models can fill evolving wetlands mapping needs and increase accuracy and efficiency of detection and prediction of sensitive wetland ecosystems, especially for heavily forested coastal wetland systems. Full article

(This article belongs to the Special Issue Women in Sensors)

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21 pages, 5172 KiB

Open AccessArticle

Human Occupancy Detection via Passive Cognitive Radio

by Jenny Liu, Huaizheng Mu, Asad Vakil, Robert Ewing, Xiaoping Shen, Erik Blasch and Jia Li

Sensors 2020, 20(15), 4248; https://0-doi-org.brum.beds.ac.uk/10.3390/s20154248 - 30 Jul 2020

Cited by 20 | Viewed by 3267

Abstract

Human occupancy detection (HOD) in an enclosed space, such as indoors or inside of a vehicle, via passive cognitive radio (CR) is a new and challenging research area. Part of the difficulty arises from the fact that a human subject cannot easily be detected due to spectrum variation. In this paper, we present an advanced HOD system that dynamically reconfigures a CR to collect passive radio frequency (RF) signals at different places of interest. Principal component analysis (PCA) and recursive feature elimination with logistic regression (RFE-LR) algorithms are applied to find the frequency bands sensitive to human occupancy when the baseline spectrum changes with locations. With the dynamically collected passive RF signals, four machine learning (ML) classifiers are applied to detect human occupancy, including support vector machine (SVM), k-nearest neighbors (KNN), decision tree (DT), and linear SVM with stochastic gradient descent (SGD) training. The experimental results show that the proposed system can accurately detect human subjects—not only in residential rooms—but also in commercial vehicles, demonstrating that passive CR is a viable technique for HOD. More specifically, the RFE-LR with SGD achieves the best results with a limited number of frequency bands. The proposed adaptive spectrum sensing method has not only enabled robust detection performance in various environments, but also improved the efficiency of the CR system in terms of speed and power consumption. Full article

(This article belongs to the Special Issue Women in Sensors)

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11 pages, 1819 KiB

Open AccessArticle

A Paper-Based Device for Ultrasensitive, Colorimetric Phosphate Detection in Seawater

by Joan M. Racicot, Teresa L. Mako, Alexander Olivelli and Mindy Levine

Sensors 2020, 20(10), 2766; https://0-doi-org.brum.beds.ac.uk/10.3390/s20102766 - 12 May 2020

Cited by 32 | Viewed by 4409

Abstract

High concentrations of certain nutrients, including phosphate, are known to lead to undesired algal growth and low dissolved oxygen levels, creating deadly conditions for organisms in marine ecosystems. The rapid and robust detection of these nutrients using a colorimetric, paper-based system that can be applied on-site is of high interest to individuals monitoring marine environments and others affected by marine ecosystem health. Several techniques for detecting phosphate have been reported previously, yet these techniques often suffer from high detection limits, reagent instability, and the need of the user to handle toxic reagents. In order to develop improved phosphate detection methods, the commonly used molybdenum blue reagents were incorporated into a paper-based, colorimetric detection system. This system benefited from improved stabilization of the molybdenum blue reagent as well as minimal user contact with toxic reagents. The colorimetric readout from the paper-based devices was analyzed and quantified using RGB analyses (via ImageJ), and resulted in the detection of phosphate at detection limits between 1.3 and 2.8 ppm in various aqueous media, including real seawater. Full article

(This article belongs to the Special Issue Women in Sensors)

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Review

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22 pages, 5522 KiB

Open AccessReview

Single Photon Avalanche Diode Arrays for Time-Resolved Raman Spectroscopy

by Francesca Madonini and Federica Villa

Sensors 2021, 21(13), 4287; https://0-doi-org.brum.beds.ac.uk/10.3390/s21134287 - 23 Jun 2021

Cited by 21 | Viewed by 4958

Abstract

The detection of peaks shifts in Raman spectroscopy enables a fingerprint reconstruction to discriminate among molecules with neither labelling nor sample preparation. Time-resolved Raman spectroscopy is an effective technique to reject the strong fluorescence background that profits from the time scale difference in the two responses: Raman photons are scattered almost instantaneously while fluorescence shows a nanoseconds time constant decay. The combination of short laser pulses with time-gated detectors enables the collection of only those photons synchronous with the pulse, thus rejecting fluorescent ones. This review addresses time-gating issues from the sensor standpoint and identifies single photon avalanche diode (SPAD) arrays as the most suitable single-photon detectors to be rapidly and precisely time-gated without bulky, complex, or expensive setups. At first, we discuss the requirements for ideal Raman SPAD arrays, particularly focusing on the design guidelines for optimized on-chip processing electronics. Then we present some existing SPAD-based architectures, featuring specific operation modes which can be usefully exploited for Raman spectroscopy. Finally, we highlight key aspects for future ultrafast Raman platforms and highly integrated sensors capable of undistorted identification of Raman peaks across many pixels. Full article

(This article belongs to the Special Issue Women in Sensors)

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43 pages, 4181 KiB

Open AccessReview

Advancement of Sensor Integrated Organ-on-Chip Devices

by Gabriel A. Clarke, Brenna X. Hartse, Amir Ehsan Niaraki Asli, Mehrnoosh Taghavimehr, Niloofar Hashemi, Mehran Abbasi Shirsavar, Reza Montazami, Nima Alimoradi, Vahid Nasirian, Lionel J. Ouedraogo and Nicole N. Hashemi

Sensors 2021, 21(4), 1367; https://0-doi-org.brum.beds.ac.uk/10.3390/s21041367 - 15 Feb 2021

Cited by 54 | Viewed by 9147

Abstract

Organ-on-chip devices have provided the pharmaceutical and tissue engineering worlds much hope since they arrived and began to grow in sophistication. However, limitations for their applicability were soon realized as they lacked real-time monitoring and sensing capabilities. The users of these devices relied solely on endpoint analysis for the results of their tests, which created a chasm in the understanding of life between the lab the natural world. However, this gap is being bridged with sensors that are integrated into organ-on-chip devices. This review goes in-depth on different sensing methods, giving examples for various research on mechanical, electrical resistance, and bead-based sensors, and the prospects of each. Furthermore, the review covers works conducted that use specific sensors for oxygen, and various metabolites to characterize cellular behavior and response in real-time. Together, the outline of these works gives a thorough analysis of the design methodology and sophistication of the current sensor integrated organ-on-chips. Full article

(This article belongs to the Special Issue Women in Sensors)

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26 pages, 2081 KiB

Open AccessReview

Porous Silicon Optical Devices: Recent Advances in Biosensing Applications

by Rosalba Moretta, Luca De Stefano, Monica Terracciano and Ilaria Rea

Sensors 2021, 21(4), 1336; https://0-doi-org.brum.beds.ac.uk/10.3390/s21041336 - 13 Feb 2021

Cited by 53 | Viewed by 5447

Abstract

This review summarizes the leading advancements in porous silicon (PSi) optical-biosensors, achieved over the past five years. The cost-effective fabrication process, the high internal surface area, the tunable pore size, and the photonic properties made the PSi an appealing transducing substrate for biosensing purposes, with applications in different research fields. Different optical PSi biosensors are reviewed and classified into four classes, based on the different biorecognition elements immobilized on the surface of the transducing material. The PL signal modulation and the effective refractive index changes of the porous matrix are the main optical transduction mechanisms discussed herein. The approaches that are commonly employed to chemically stabilize and functionalize the PSi surface are described. Full article

(This article belongs to the Special Issue Women in Sensors)

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25 pages, 17856 KiB

Open AccessReview

DNA Electrochemical Biosensors for In Situ Probing of Pharmaceutical Drug Oxidative DNA Damage

by Ana-Maria Chiorcea-Paquim and Ana Maria Oliveira-Brett

Sensors 2021, 21(4), 1125; https://0-doi-org.brum.beds.ac.uk/10.3390/s21041125 - 05 Feb 2021

Cited by 28 | Viewed by 4205

Abstract

Deoxyribonucleic acid (DNA) electrochemical biosensors are devices that incorporate immobilized DNA as a molecular recognition element on the electrode surface, and enable probing in situ the oxidative DNA damage. A wide range of DNA electrochemical biosensor analytical and biotechnological applications in pharmacology are foreseen, due to their ability to determine in situ and in real-time the DNA interaction mechanisms with pharmaceutical drugs, as well as with their degradation products, redox reaction products, and metabolites, and due to their capacity to achieve quantitative electroanalytical evaluation of the drugs, with high sensitivity, short time of analysis, and low cost. This review presents the design and applications of label-free DNA electrochemical biosensors that use DNA direct electrochemical oxidation to detect oxidative DNA damage. The DNA electrochemical biosensor development, from the viewpoint of electrochemical and atomic force microscopy (AFM) characterization, and the bottom-up immobilization of DNA nanostructures at the electrode surface, are described. Applications of DNA electrochemical biosensors that enable the label-free detection of DNA interactions with pharmaceutical compounds, such as acridine derivatives, alkaloids, alkylating agents, alkylphosphocholines, antibiotics, antimetabolites, kinase inhibitors, immunomodulatory agents, metal complexes, nucleoside analogs, and phenolic compounds, which can be used in drug analysis and drug discovery, and may lead to future screening systems, are reviewed. Full article

(This article belongs to the Special Issue Women in Sensors)

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Other

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11 pages, 3606 KiB

Open AccessTechnical Note

Development of an MFL Coil Sensor for Testing Pipes in Extreme Temperature Conditions

by Nagu Sathappan, Mohammad Osman Tokhi, Liam Penaluna, Zhangfang Zhao, Fang Duan, Gholamhossein Shirkoohi and Aman Kaur

Sensors 2021, 21(9), 3033; https://0-doi-org.brum.beds.ac.uk/10.3390/s21093033 - 26 Apr 2021

Cited by 5 | Viewed by 2937

Abstract

This paper aims to design a coil sensor for corrosion monitoring of industrial pipes that could detect variations in thickness using the MFL (Magnetic Flux Leakage) technique. An MFL coil sensor is designed and tested with pipe sample thicknesses of 2, 4, 6, and 8 mm based on the magnetic field effect of ferrite cores. Moreover, a measurement setup for analysing pipe samples up to a temperature of 200° Celsius is suggested. Experimental results reveal that the MFL coil sensor can fulfil the requirements for MFL testing of pipes in high temperature conditions, and that the precision of MFL monitoring of pipes to detect corrosion at high temperatures can be improved significantly. Full article

(This article belongs to the Special Issue Women in Sensors)

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