Sensors

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16 pages, 6135 KiB

Open AccessArticle

Image Sensors for Wave Monitoring in Shore Protection: Characterization through a Machine Learning Algorithm

by Aimé Lay-Ekuakille, John Peter Djungha Okitadiowo, Diana Di Luccio, Maurizio Palmisano, Giorgio Budillon, Guido Benassai and Sabino Maggi

Sensors 2021, 21(12), 4203; https://doi.org/10.3390/s21124203 - 18 Jun 2021

Cited by 3 | Viewed by 2697

Abstract

Waves propagating on the water surface can be considered as propagating in a dispersive medium, where gravity and surface tension at the air–water interface act as restoring forces. The velocity at which energy is transported in water waves is defined by the group [...] Read more.

Waves propagating on the water surface can be considered as propagating in a dispersive medium, where gravity and surface tension at the air–water interface act as restoring forces. The velocity at which energy is transported in water waves is defined by the group velocity. The paper reports the use of video-camera observations to study the impact of water waves on an urban shore. The video-monitoring system consists of two separate cameras equipped with progressive RGB CMOS sensors that allow 1080p HDTV video recording. The sensing system delivers video signals that are processed by a machine learning technique. The scope of the research is to identify features of water waves that cannot be normally observed. First, a conventional modelling was performed using data delivered by image sensors together with additional data such as temperature, and wind speed, measured with dedicated sensors. Stealth waves are detected, as are the inverting phenomena encompassed in waves. This latter phenomenon can be detected only through machine learning. This double approach allows us to prevent extreme events that can take place in offshore and onshore areas. Full article

(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)

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14 pages, 4828 KiB

Open AccessArticle

Evaluation of the Effects of Mobile Smart Object to Boost IoT Network Synchronization

by Francesco Lamonaca and Domenico Luca Carnì

Sensors 2021, 21(12), 3957; https://doi.org/10.3390/s21123957 - 8 Jun 2021

Cited by 8 | Viewed by 2373

Abstract

This paper deals with the synchronization of Mobile Smart Objects (MSOs). Today, this scenario is becoming typical in Industrial IoT applications due to the plethora of MSOs available as robots, drones and wearables, equipped by sensors making them measurement instruments cooperating in distributed [...] Read more.

This paper deals with the synchronization of Mobile Smart Objects (MSOs). Today, this scenario is becoming typical in Industrial IoT applications due to the plethora of MSOs available as robots, drones and wearables, equipped by sensors making them measurement instruments cooperating in distributed measurement systems. In this context, the synchronization accuracy is directly tied with the accuracy of the performed measurements. In hierarchical synchronization approaches, the presence of an MSO makes the network topology time varying, and this could prevent the synchronization of the whole network. Peer to peer approaches do not need node hierarchy to synchronize but could not converge to a common sense of time. To overcome these challenges, this paper proposes a consensus-based approach for which the convergence to a common sense of time is here demonstrated. The proposal deploys the MSO to bring the common sense of time from an SO to another, establishing new paths among SOs. The new paths are temporary and depend on the MSO’s route. In the paper, the influence of the MSO’s route on the synchronization accuracy σ and the time interval to synchronize all the SOs ∆_TIS is investigated, also. The mathematical proof, the simulations and the experimental tests confirm that the MSO can reduce both the values of σ and ∆_TIS, because the new connections introduced by the MSO can boost the exchange of information among SOs. Consequently, the criteria to a priori select the route ameliorating σ and ∆_TIS values are proposed. Full article

(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)

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14 pages, 2392 KiB

Open AccessArticle

Sensing Optimum in the Raw: Leveraging the Raw-Data Imaging Capabilities of Raspberry Pi for Diagnostics Applications

by Alessandro Tonelli, Veronica Mangia, Alessandro Candiani, Francesco Pasquali, Tiziana Jessica Mangiaracina, Alessandro Grazioli, Michele Sozzi, Davide Gorni, Simona Bussolati, Annamaria Cucinotta, Giuseppina Basini and Stefano Selleri

Sensors 2021, 21(10), 3552; https://doi.org/10.3390/s21103552 - 20 May 2021

Cited by 3 | Viewed by 6291

Abstract

Single-board computers (SBCs) and microcontroller boards (MCBs) are extensively used nowadays as prototyping platforms to accomplish innovative tasks. Very recently, implementations of these devices for diagnostics applications are rapidly gaining ground for research and educational purposes. Among the available solutions, Raspberry Pi represents [...] Read more.

Single-board computers (SBCs) and microcontroller boards (MCBs) are extensively used nowadays as prototyping platforms to accomplish innovative tasks. Very recently, implementations of these devices for diagnostics applications are rapidly gaining ground for research and educational purposes. Among the available solutions, Raspberry Pi represents one of the most used SBCs. In the present work, two setups based on Raspberry Pi and its CMOS-based camera (a 3D-printed device and an adaptation of a commercial product named We-Lab) were investigated as diagnostic instruments. Different camera elaboration processes were investigated, showing how direct access to the 10-bit raw data acquired from the sensor before downstream imaging processes could be beneficial for photometric applications. The developed solution was successfully applied to the evaluation of the oxidative stress using two commercial kits (d-ROM Fast; PAT). We suggest the analysis of raw data applied to SBC and MCB platforms in order to improve results. Full article

(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)

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17 pages, 3309 KiB

Open AccessArticle

Noise Floor Reduction in Frequency Delta-Sigma Modulation Microphone Sensors

by Koichi Maezawa, Masayuki Mori and Hiroya Andoh

Sensors 2021, 21(10), 3470; https://doi.org/10.3390/s21103470 - 16 May 2021

Cited by 2 | Viewed by 3442

Abstract

Frequency delta-sigma modulator (FDSM) employing a variable frequency oscillator is a novel replacement of the classical delta-sigma modulators. This is advantageous for application to sensors, because an ADC can be intrinsically integrated with the sensors. We have already proposed to use this technique [...] Read more.

Frequency delta-sigma modulator (FDSM) employing a variable frequency oscillator is a novel replacement of the classical delta-sigma modulators. This is advantageous for application to sensors, because an ADC can be intrinsically integrated with the sensors. We have already proposed to use this technique to various sensors. However, the signal-to-noise ratio was significantly degraded by noise floor, in the previous papers. In this paper, we have investigated the origin of the noise floor in the FDSM microphone sensors as a promising example. It was demonstrated that improving the phase noise of the oscillator can drastically reduce the noise floor. For this reduction we improved the Q-factor of the cavity resonator, and the design of the oscillator circuit. With these improvements, the phase noise, and, hence, the noise floor, were improved by approximately 40 dB. In addition, we obtained an SNR of 57 dB for 114 dBSPL sound input with 96 kHz bandwidth, which corresponds to the dynamic range of 87 dB for maximum 140 dBSPL. A much larger dynamic range of around 120 dB is expected by increasing the sampling rate and decreasing the Al diaphragm thickness. These results also indicate the promise of the FDSM to varieties of physical sensors. Full article

(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)

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15 pages, 3829 KiB

Open AccessArticle

Multisensorial Assessment of Laser Effects on Shellac Applied on Wall Paintings

by Jana Striova, Raffaella Fontana, Ilaria Barbetti, Luca Pezzati, Annamaria Fedele and Cristiano Riminesi

Sensors 2021, 21(10), 3354; https://doi.org/10.3390/s21103354 - 12 May 2021

Cited by 10 | Viewed by 2729

Abstract

The assessment of five different laser treatments in the conservation of wall paintings was devised on the basis of the surface temperature monitoring by infrared thermography (IRT), ultraviolet-induced fluorescence-visible (UV-VIS) imaging, and optical coherence tomography (OCT). A series of yttrium-aluminum-garnet (YAG) lasers were [...] Read more.

The assessment of five different laser treatments in the conservation of wall paintings was devised on the basis of the surface temperature monitoring by infrared thermography (IRT), ultraviolet-induced fluorescence-visible (UV-VIS) imaging, and optical coherence tomography (OCT). A series of yttrium-aluminum-garnet (YAG) lasers were tested for removal of shellac layers from wall painting mock-ups. The mock-ups were realized as buon fresco with different mineral based pigments (earths and iron oxide) on a lime- and sand-based mortar. After the carbonatation process, all the samples were treated with shellac (5% in ethanol). The effects of neodymium (Nd):YAG, holmium (Ho):YAG, and erbium (Er):YAG laser sources, in different operative modes, on average temperature of the surface, color, and morphology were inspected with complementary sensors. The results show the necessity to adopt a combined approach in establishing safe laser operating conditions to avoid any undesired effects induced on the artefacts by the laser treatments. We demonstrate, for the first time, the performance of the Ho:YAG laser in the removal of a conservation treatment. Full article

(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)

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14 pages, 3174 KiB

Open AccessCommunication

Humidity Sensing by Chitosan-Coated Fibre Bragg Gratings (FBG)

by Rosaria D’Amato, Andrea Polimadei, Gaetano Terranova and Michele Arturo Caponero

Sensors 2021, 21(10), 3348; https://doi.org/10.3390/s21103348 - 12 May 2021

Cited by 26 | Viewed by 3650

Abstract

In this work, we report novel relative humidity sensors realized by functionalising fibre Bragg gratings with chitosan, a moisture-sensitive biopolymer never used before for this kind of fibre optic sensor. The swelling capacity of chitosan is fundamental to the sensing mechanism. Different samples [...] Read more.

In this work, we report novel relative humidity sensors realized by functionalising fibre Bragg gratings with chitosan, a moisture-sensitive biopolymer never used before for this kind of fibre optic sensor. The swelling capacity of chitosan is fundamental to the sensing mechanism. Different samples were fabricated, testing the influence of coating design and deposition procedure on sensor performance. The sensitivity of the sensors was measured in an airtight humidity-controlled chamber using saturated chemical salt solutions. The best result in terms of sensitivity was obtained for a sensor produced on filter paper substrate. Tests for each design were performed in the environment, lasted several days, and all designs were independently re-tested at different seasons of the year. The produced sensors closely followed the ambient humidity variation common to the 24-h circadian cycle. Full article

(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)

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8 pages, 1841 KiB

Open AccessCommunication

Nanomechanical Molecular Mass Sensing Using Suspended Microchannel Resonators

by Alberto Martín-Pérez, Daniel Ramos, Javier Tamayo and Montserrat Calleja

Sensors 2021, 21(10), 3337; https://doi.org/10.3390/s21103337 - 11 May 2021

Cited by 7 | Viewed by 3735

Abstract

In this work we study the different phenomena taking place when a hydrostatic pressure is applied in the inner fluid of a suspended microchannel resonator. Additionally to pressure-induced stiffness terms, we have theoretically predicted and experimentally demonstrated that the pressure also induces mass [...] Read more.

In this work we study the different phenomena taking place when a hydrostatic pressure is applied in the inner fluid of a suspended microchannel resonator. Additionally to pressure-induced stiffness terms, we have theoretically predicted and experimentally demonstrated that the pressure also induces mass effects which depend on both the applied pressure and the fluid properties. We have used these phenomena to characterize the frequency response of the device as a function of the fluid compressibility and molecular masses of different fluids ranging from liquids to gases. The proposed device in this work can measure the mass density of an unknown liquid sample with a resolution of 0.7 µg/mL and perform gas mixtures characterization by measuring its average molecular mass with a resolution of 0.01 atomic mass units. Full article

(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)

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37 pages, 6870 KiB

Open AccessArticle

The Role of Global Appearance of Omnidirectional Images in Relative Distance and Orientation Retrieval

by Vicente Román, Luis Payá, Adrián Peidró, Mónica Ballesta and Oscar Reinoso

Sensors 2021, 21(10), 3327; https://doi.org/10.3390/s21103327 - 11 May 2021

Cited by 3 | Viewed by 2858

Abstract

Over the last few years, mobile robotics has experienced a great development thanks to the wide variety of problems that can be solved with this technology. An autonomous mobile robot must be able to operate in a priori unknown environments, planning its trajectory [...] Read more.

Over the last few years, mobile robotics has experienced a great development thanks to the wide variety of problems that can be solved with this technology. An autonomous mobile robot must be able to operate in a priori unknown environments, planning its trajectory and navigating to the required target points. With this aim, it is crucial solving the mapping and localization problems with accuracy and acceptable computational cost. The use of omnidirectional vision systems has emerged as a robust choice thanks to the big quantity of information they can extract from the environment. The images must be processed to obtain relevant information that permits solving robustly the mapping and localization problems. The classical frameworks to address this problem are based on the extraction, description and tracking of local features or landmarks. However, more recently, a new family of methods has emerged as a robust alternative in mobile robotics. It consists of describing each image as a whole, what leads to conceptually simpler algorithms. While methods based on local features have been extensively studied and compared in the literature, those based on global appearance still merit a deep study to uncover their performance. In this work, a comparative evaluation of six global-appearance description techniques in localization tasks is carried out, both in terms of accuracy and computational cost. Some sets of images captured in a real environment are used with this aim, including some typical phenomena such as changes in lighting conditions, visual aliasing, partial occlusions and noise. Full article

(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)

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21 pages, 5197 KiB

Open AccessArticle

Co-Training for Deep Object Detection: Comparing Single-Modal and Multi-Modal Approaches

by Jose L. Gómez, Gabriel Villalonga and Antonio M. López

Sensors 2021, 21(9), 3185; https://doi.org/10.3390/s21093185 - 4 May 2021

Cited by 6 | Viewed by 2752

Abstract

Top-performing computer vision models are powered by convolutional neural networks (CNNs). Training an accurate CNN highly depends on both the raw sensor data and their associated ground truth (GT). Collecting such GT is usually done through human labeling, which is time-consuming and does [...] Read more.

Top-performing computer vision models are powered by convolutional neural networks (CNNs). Training an accurate CNN highly depends on both the raw sensor data and their associated ground truth (GT). Collecting such GT is usually done through human labeling, which is time-consuming and does not scale as we wish. This data-labeling bottleneck may be intensified due to domain shifts among image sensors, which could force per-sensor data labeling. In this paper, we focus on the use of co-training, a semi-supervised learning (SSL) method, for obtaining self-labeled object bounding boxes (BBs), i.e., the GT to train deep object detectors. In particular, we assess the goodness of multi-modal co-training by relying on two different views of an image, namely, appearance (RGB) and estimated depth (D). Moreover, we compare appearance-based single-modal co-training with multi-modal. Our results suggest that in a standard SSL setting (no domain shift, a few human-labeled data) and under virtual-to-real domain shift (many virtual-world labeled data, no human-labeled data) multi-modal co-training outperforms single-modal. In the latter case, by performing GAN-based domain translation both co-training modalities are on par, at least when using an off-the-shelf depth estimation model not specifically trained on the translated images. Full article

(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)

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26 pages, 4488 KiB

Open AccessArticle

Microwave Sensors for In Situ Monitoring of Trace Metals in Polluted Water

by Ilaria Frau, Stephen Wylie, Patrick Byrne, Patrizia Onnis, Jeff Cullen, Alex Mason and Olga Korostynska

Sensors 2021, 21(9), 3147; https://doi.org/10.3390/s21093147 - 1 May 2021

Cited by 29 | Viewed by 6034

Abstract

Thousands of pollutants are threatening our water supply, putting at risk human and environmental health. Between them, trace metals are of significant concern, due to their high toxicity at low concentrations. Abandoned mining areas are globally one of the major sources of toxic [...] Read more.

Thousands of pollutants are threatening our water supply, putting at risk human and environmental health. Between them, trace metals are of significant concern, due to their high toxicity at low concentrations. Abandoned mining areas are globally one of the major sources of toxic metals. Nowadays, no method can guarantee an immediate response for quantifying these pollutants. In this work, a novel technique based on microwave spectroscopy and planar sensors for in situ real-time monitoring of water quality is described. The sensors were developed to directly probe water samples, and in situ trial measurements were performed in freshwater in four polluted mining areas in the UK. Planar microwave sensors were able to detect the water pollution level with an immediate response specifically depicted at three resonant peaks in the GHz range. To the authors’ best knowledge, this is the first time that planar microwave sensors were tested in situ, demonstrating the ability to use this method for classifying more and less polluted water using a multiple-peak approach. Full article

(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)

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9 pages, 1485 KiB

Open AccessCommunication

A Technique for Improving the Precision of the Direct Measurement of Junction Temperature in Power Light-Emitting Diodes

by Demetrio Iero, Massimo Merenda, Riccardo Carotenuto, Giovanni Pangallo, Sandro Rao, Gheorghe Brezeanu and Francesco G. Della Corte

Sensors 2021, 21(9), 3113; https://doi.org/10.3390/s21093113 - 29 Apr 2021

Cited by 5 | Viewed by 2861

Abstract

Extending the lifetime of power light-emitting diodes (LEDs) is achievable if proper control methods are implemented to reduce the side effects of an excessive junction temperature, T_J. The accuracy of state-of-the-art LED junction temperature monitoring techniques is negatively affected by several [...] Read more.

Extending the lifetime of power light-emitting diodes (LEDs) is achievable if proper control methods are implemented to reduce the side effects of an excessive junction temperature, T_J. The accuracy of state-of-the-art LED junction temperature monitoring techniques is negatively affected by several factors, such as the use of external sensors, calibration procedures, devices aging, and technological diversity among samples with the same part number. Here, a novel method is proposed, indeed based on the well-known technique consisting in tracking the LED forward voltage drop when a fixed forward current is imposed but exploiting the voltage variation with respect to room temperature. This method, which limits the effects of sample heterogeneity, is applied to a set of ten commercial devices. The method led to an effective reduction of the measurement error, which was below 1 °C. Full article

(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)

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20 pages, 9146 KiB

Open AccessCommunication

Multiscale Analysis of Solar Loading Thermographic Signals for Wall Structure Inspection

by Katherine Tu, Clemente Ibarra-Castanedo, Stefano Sfarra, Yuan Yao and Xavier P. V. Maldague

Sensors 2021, 21(8), 2806; https://doi.org/10.3390/s21082806 - 16 Apr 2021

Cited by 6 | Viewed by 2366

Abstract

Infrared thermography has been widely adopted in many applications for material structure inspection, where data analysis methods are often implemented to elaborate raw thermal data and to characterize material structural properties. Herein, a multiscale thermographic data analysis framework is proposed and applied to [...] Read more.

Infrared thermography has been widely adopted in many applications for material structure inspection, where data analysis methods are often implemented to elaborate raw thermal data and to characterize material structural properties. Herein, a multiscale thermographic data analysis framework is proposed and applied to building structure inspection. In detail, thermograms are first collected by conducting solar loading thermography, which are then decomposed into several intrinsic mode functions under different spatial scales by multidimensional ensemble empirical mode decomposition. At each scale, principal component analysis (PCA) is implemented for feature extraction. By visualizing the loading vectors of PCA, the important building structures are highlighted. Compared with principal component thermography that applies PCA directly to raw thermal data, the proposed multiscale analysis method is able to zoom in on different types of structural features. Full article

(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)

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16 pages, 4755 KiB

Open AccessArticle

High-Order Wave-Damage Interaction Coefficients (WDIC) Extracted through Modal Decomposition

by Hanfei Mei and Victor Giurgiutiu

Sensors 2021, 21(8), 2749; https://doi.org/10.3390/s21082749 - 13 Apr 2021

Cited by 7 | Viewed by 2678

Abstract

This paper presents a new technique for the extraction of high-order wave-damage interaction coefficients (WDIC) through modal decomposition. The frequency and direction dependent complex-valued WDIC are used to model the scattering and mode conversion phenomena of guided wave interaction with damage. These coefficients [...] Read more.

This paper presents a new technique for the extraction of high-order wave-damage interaction coefficients (WDIC) through modal decomposition. The frequency and direction dependent complex-valued WDIC are used to model the scattering and mode conversion phenomena of guided wave interaction with damage. These coefficients are extracted from the harmonic analysis of local finite element model (FEM) mesh with non-reflective boundaries (NRB) and they are capable of describing the amplitude and phase of the scattered waves as a function of frequency and direction. To extract the WDIC of each wave mode, all the possible propagating wave modes are considered to be scattered simultaneously from the damage and propagate independently. Formulated in frequency domain, the proposed method is highly efficient, providing an overdetermined equation system for the calculation of mode participation factors, i.e., WDIC of each mode. Case studies in a 6-mm aluminum plate were carried out to validate the WDIC of: (1) a through-thickness hole and (2) a sub-surface crack. At higher frequency, scattered waves of high-order modes will appear and their WDIC can be successfully extracted through the modal decomposition. Full article

(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)

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9 pages, 1211 KiB

Open AccessCommunication

Bias Voltage Dependence of Sensing Characteristics in Tunneling Magnetoresistance Sensors

by Piotr Wiśniowski, Maciej Nawrocki, Jerzy Wrona, Susana Cardoso and Paulo. P. Freitas

Sensors 2021, 21(7), 2495; https://doi.org/10.3390/s21072495 - 3 Apr 2021

Cited by 3 | Viewed by 4179

Abstract

One of the characteristic features of tunneling magnetoresistance (TMR) sensors is a strong influence of bias voltage on tunneling current. Since fundamental sensing characteristics of the sensors are primarily determined by the tunneling current, the bias voltage should impact these characteristics. Previous research [...] Read more.

One of the characteristic features of tunneling magnetoresistance (TMR) sensors is a strong influence of bias voltage on tunneling current. Since fundamental sensing characteristics of the sensors are primarily determined by the tunneling current, the bias voltage should impact these characteristics. Previous research has indeed showed the influence of the bias voltage on the magnetic field detection and sensitivity. However, the effect has not been investigated for nonlinearity and hysteresis and the influence of bias voltage polarity has not yet been addressed. Therefore, this paper systematically investigates the dependence of field sensitivity, nonlinearity, hysteresis and magnetic field detection of CoFeB/MgO/CoFeB-based magnetoresistance sensors on bias voltage magnitude and polarity. The sensitivity and field detection of all sensors improved significantly with the bias, whereas the nonlinearity and hysteresis deteriorated. The sensitivity increased considerably (up to 32 times) and linearly with bias up to 0.6 V. The field detection also decreased substantially (up 3.9 times) with bias and exhibited the minimum values for the same magnitude under both polarities. Significant and linear increases with bias were also observed for nonlinearity (up to 26 times) and hysteresis (up to 33 times). Moreover, not only the voltage magnitude but also the polarity had a significant effect on the sensing characteristics. This significant, linear and simultaneous effect of improvement and deterioration of the sensing characteristics with bias indicates that both bias voltage magnitude and polarity are key factors in the control and modification of these characteristics. Full article

(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)

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15 pages, 7483 KiB

Open AccessArticle

In Vivo Quantitative Vasculature Segmentation and Assessment for Photodynamic Therapy Process Monitoring Using Photoacoustic Microscopy

by Thi Thao Mai, Su Woong Yoo, Suhyun Park, Jin Young Kim, Kang-Ho Choi, Chulhong Kim, Seong Young Kwon, Jung-Joon Min and Changho Lee

Sensors 2021, 21(5), 1776; https://doi.org/10.3390/s21051776 - 4 Mar 2021

Cited by 29 | Viewed by 5038

Abstract

Vascular damage is one of the therapeutic mechanisms of photodynamic therapy (PDT). In particular, short-term PDT treatments can effectively destroy malignant lesions while minimizing damage to nonmalignant tissue. In this study, we investigate the feasibility of label-free quantitative photoacoustic microscopy (PAM) for monitoring [...] Read more.

Vascular damage is one of the therapeutic mechanisms of photodynamic therapy (PDT). In particular, short-term PDT treatments can effectively destroy malignant lesions while minimizing damage to nonmalignant tissue. In this study, we investigate the feasibility of label-free quantitative photoacoustic microscopy (PAM) for monitoring the vasculature changes under the effect of PDT in mouse ear melanoma tumors. In particular, quantitative vasculature evaluation was conducted based on Hessian filter segmentation. Three-dimensional morphological PAM and depth-resolved images before and after PDT treatment were acquired. In addition, five quantitative vasculature parameters, including the PA signal, vessel diameter, vessel density, perfused vessel density, and vessel complexity, were analyzed to evaluate the influence of PDT on four different areas: Two melanoma tumors, and control and normal vessel areas. The quantitative and qualitative results successfully demonstrated the potential of the proposed PAM-based quantitative approach to evaluate the effectiveness of the PDT method. Full article

(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)

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18 pages, 10190 KiB

Open AccessArticle

Enhancing Solid State LiDAR Mapping with a 2D Spinning LiDAR in Urban Scenario SLAM on Ground Vehicles

by Weichen Wei, Bijan Shirinzadeh, Rohan Nowell, Mohammadali Ghafarian, Mohamed M. A. Ammar and Tianyao Shen

Sensors 2021, 21(5), 1773; https://doi.org/10.3390/s21051773 - 4 Mar 2021

Cited by 15 | Viewed by 5916

Abstract

Solid-State LiDAR (SSL) takes an increasing share of the LiDAR market. Compared with traditional spinning LiDAR, SSLs are more compact, energy-efficient and cost-effective. Generally, the current study of SSL mapping is limited to adapting existing SLAM algorithms to an SSL sensor. However, compared [...] Read more.

Solid-State LiDAR (SSL) takes an increasing share of the LiDAR market. Compared with traditional spinning LiDAR, SSLs are more compact, energy-efficient and cost-effective. Generally, the current study of SSL mapping is limited to adapting existing SLAM algorithms to an SSL sensor. However, compared with spinning LiDARs, SSLs are different in terms of their irregular scan patterns and limited FOV. Directly applying existing SLAM approaches on them often increase the instability of a mapping process. This study proposes a systematic design, which consists of a dual-LiDAR mapping system and a three DOF interpolated six DOF odometry. For dual-LiDAR mapping, this work uses a 2D LiDAR to enhance a 3D SSL performance on a ground vehicle platform. The proposed system takes a 2D LiDAR to preprocess the scanning field into a number of feature sections according to the curvatures on the 2D fraction. Subsequently, this section information is passed to 3D SSL for direction feature selection. Additionally, this work proposes an odometry interpolation method which uses both LiDARs to generate two separated odometries. The proposed odometry interpolation method selectively determines the appropriate odometry information to update the system state under challenging conditions. Experiments are conducted in different scenarios. The results proves that the proposed approach is able to utilise 12 times more corner features from the environment than the comparied method, thus results in a demonstrable improvement in its absolute position error. Full article

(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)

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14 pages, 1466 KiB

Open AccessArticle

Smartphone-Based Prediction Model for Postoperative Cardiac Surgery Outcomes Using Preoperative Gait and Posture Measures

by Rahul Soangra and Thurmon Lockhart

Sensors 2021, 21(5), 1704; https://doi.org/10.3390/s21051704 - 2 Mar 2021

Cited by 9 | Viewed by 3843

Abstract

Gait speed assessment increases the predictive value of mortality and morbidity following older adults’ cardiac surgery. The purpose of this study was to improve clinical assessment and prediction of mortality and morbidity among older patients undergoing cardiac surgery through the identification of the [...] Read more.

Gait speed assessment increases the predictive value of mortality and morbidity following older adults’ cardiac surgery. The purpose of this study was to improve clinical assessment and prediction of mortality and morbidity among older patients undergoing cardiac surgery through the identification of the relationships between preoperative gait and postural stability characteristics utilizing a noninvasive-wearable mobile phone device and postoperative cardiac surgical outcomes. This research was a prospective study of ambulatory patients aged over 70 years undergoing non-emergent cardiac surgery. Sixteen older adults with cardiovascular disease (Age 76.1 ± 3.6 years) scheduled for cardiac surgery within the next 24 h were recruited for this study. As per the Society of Thoracic Surgeons (STS) recommendation guidelines, eight of the cardiovascular disease (CVD) patients were classified as frail (prone to adverse outcomes with gait speed ≤0.833 m/s) and the remaining eight patients as non-frail (gait speed >0.833 m/s). Treating physicians and patients were blinded to gait and posture assessment results not to influence the decision to proceed with surgery or postoperative management. Follow-ups regarding patient outcomes were continued until patients were discharged or transferred from the hospital, at which time data regarding outcomes were extracted from the records. In the preoperative setting, patients performed the 5-m walk and stand still for 30 s in the clinic while wearing a mobile phone with a customized app “Lockhart Monitor” available at iOS App Store. Systematic evaluations of different gait and posture measures identified a subset of smartphone measures most sensitive to differences in two groups (frail versus non-frail) with adverse postoperative outcomes (morbidity/mortality). A regression model based on these smartphone measures tested positive on five CVD patients. Thus, clinical settings can readily utilize mobile technology, and the proposed regression model can predict adverse postoperative outcomes such as morbidity or mortality events. Full article

(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)

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22 pages, 16927 KiB

Open AccessArticle

Health Monitoring of Large-Scale Civil Structures: An Approach Based on Data Partitioning and Classical Multidimensional Scaling

by Alireza Entezami, Hassan Sarmadi, Behshid Behkamal and Stefano Mariani

Sensors 2021, 21(5), 1646; https://doi.org/10.3390/s21051646 - 26 Feb 2021

Cited by 28 | Viewed by 4048

Abstract

A major challenge in structural health monitoring (SHM) is the efficient handling of big data, namely of high-dimensional datasets, when damage detection under environmental variability is being assessed. To address this issue, a novel data-driven approach to early damage detection is proposed here. [...] Read more.

A major challenge in structural health monitoring (SHM) is the efficient handling of big data, namely of high-dimensional datasets, when damage detection under environmental variability is being assessed. To address this issue, a novel data-driven approach to early damage detection is proposed here. The approach is based on an efficient partitioning of the dataset, gathering the sensor recordings, and on classical multidimensional scaling (CMDS). The partitioning procedure aims at moving towards a low-dimensional feature space; the CMDS algorithm is instead exploited to set the coordinates in the mentioned low-dimensional space, and define damage indices through norms of the said coordinates. The proposed approach is shown to efficiently and robustly address the challenges linked to high-dimensional datasets and environmental variability. Results related to two large-scale test cases are reported: the ASCE structure, and the Z24 bridge. A high sensitivity to damage and a limited (if any) number of false alarms and false detections are reported, testifying the efficacy of the proposed data-driven approach. Full article

(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)

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15 pages, 2923 KiB

Open AccessArticle

Remote Reflectivity Sensor for Industrial Applications

by Federico Cavedo, Parisa Esmaili and Michele Norgia

Sensors 2021, 21(4), 1301; https://doi.org/10.3390/s21041301 - 11 Feb 2021

Cited by 2 | Viewed by 2659

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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14 pages, 4963 KiB

Open AccessArticle

Synchronized Hardware-Registered VIS-NIR Imaging Spectroscopy and 3D Sensing on a Fresco by Botticelli

by Jana Striova, Luca Pezzati, Enrico Pampaloni and Raffaella Fontana

Sensors 2021, 21(4), 1287; https://doi.org/10.3390/s21041287 - 11 Feb 2021

Cited by 5 | Viewed by 2864

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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17 pages, 2520 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Toward the Use of Temporary Tattoo Electrodes for Impedancemetric Respiration Monitoring and Other Electrophysiological Recordings on Skin

by Silvia Taccola, Aliria Poliziani, Daniele Santonocito, Alessio Mondini, Christian Denk, Alessandro Noriaki Ide, Markus Oberparleiter, Francesco Greco and Virgilio Mattoli

Sensors 2021, 21(4), 1197; https://doi.org/10.3390/s21041197 - 8 Feb 2021

Cited by 28 | Viewed by 6791

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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12 pages, 5005 KiB

Open AccessArticle

Acoustic Emission Signal Entropy as a Means to Estimate Loads in Fiber Reinforced Polymer Rods

by Mohammadhadi Shateri, Maha Ghaib, Dagmar Svecova and Douglas Thomson

Sensors 2021, 21(4), 1089; https://doi.org/10.3390/s21041089 - 5 Feb 2021

Cited by 3 | Viewed by 2561

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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15 pages, 34275 KiB

Open AccessArticle

A Lightweight Exoskeleton-Based Portable Gait Data Collection System

by Md Rejwanul Haque, Masudul H. Imtiaz, Samuel T. Kwak, Edward Sazonov, Young-Hui Chang and Xiangrong Shen

Sensors 2021, 21(3), 781; https://doi.org/10.3390/s21030781 - 24 Jan 2021

Cited by 16 | Viewed by 6245

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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16 pages, 1504 KiB

Open AccessArticle

Inferring the Driver’s Lane Change Intention through LiDAR-Based Environment Analysis Using Convolutional Neural Networks

by Alberto Díaz-Álvarez, Miguel Clavijo, Felipe Jiménez and Francisco Serradilla

Sensors 2021, 21(2), 475; https://doi.org/10.3390/s21020475 - 11 Jan 2021

Cited by 15 | Viewed by 3552

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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15 pages, 6307 KiB

Open AccessArticle

In-Situ Estimation of Soil Water Retention Curve in Silt Loam and Loamy Sand Soils at Different Soil Depths

by Reem Zeitoun, Mark Vandergeest, Hiteshkumar Bhogilal Vasava, Pedro Vitor Ferrari Machado, Sean Jordan, Gary Parkin, Claudia Wagner-Riddle and Asim Biswas

Sensors 2021, 21(2), 447; https://doi.org/10.3390/s21020447 - 10 Jan 2021

Cited by 17 | Viewed by 5913

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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30 pages, 73208 KiB

Open AccessArticle

Twelve-Year Analysis of NO₂ Concentration Measurements at Belisario Station (Quito, Ecuador) Using Statistical Inference Techniques

by Wilmar Hernandez and Alfredo Mendez

Sensors 2020, 20(20), 5831; https://doi.org/10.3390/s20205831 - 15 Oct 2020

Cited by 5 | Viewed by 2659

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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17 pages, 1932 KiB

Open AccessArticle

Deep Physiological Model for Blood Glucose Prediction in T1DM Patients

by Mario Munoz-Organero

Sensors 2020, 20(14), 3896; https://doi.org/10.3390/s20143896 - 13 Jul 2020

Cited by 41 | Viewed by 7519

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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14 pages, 4861 KiB

Open AccessArticle

Technique and Circuit for Contactless Readout of Piezoelectric MEMS Resonator Sensors

by Marco Baù, Marco Ferrari, Habiba Begum, Abid Ali, Joshua E.-Y. Lee and Vittorio Ferrari

Sensors 2020, 20(12), 3483; https://doi.org/10.3390/s20123483 - 19 Jun 2020

Cited by 6 | Viewed by 4594

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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16 pages, 3352 KiB

Open AccessArticle

Polymer Optical Fiber-Based Integrated Instrumentation in a Robot-Assisted Rehabilitation Smart Environment: A Proof of Concept

by Arnaldo Leal-Junior, Leticia Avellar, Jonathan Jaimes, Camilo Díaz, Wilian dos Santos, Adriano A. G. Siqueira, Maria José Pontes, Carlos Marques and Anselmo Frizera

Sensors 2020, 20(11), 3199; https://doi.org/10.3390/s20113199 - 4 Jun 2020

Cited by 19 | Viewed by 4053

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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31 pages, 3710 KiB

Open AccessEditor’s ChoiceReview

Recent Advances in Transducers for Intravascular Ultrasound (IVUS) Imaging

by Chang Peng, Huaiyu Wu, Seungsoo Kim, Xuming Dai and Xiaoning Jiang

Sensors 2021, 21(10), 3540; https://doi.org/10.3390/s21103540 - 19 May 2021

Cited by 90 | Viewed by 19670

Abstract

As a well-known medical imaging methodology, intravascular ultrasound (IVUS) imaging plays a critical role in diagnosis, treatment guidance and post-treatment assessment of coronary artery diseases. By cannulating a miniature ultrasound transducer mounted catheter into an artery, the vessel lumen opening, vessel wall morphology [...] Read more.

As a well-known medical imaging methodology, intravascular ultrasound (IVUS) imaging plays a critical role in diagnosis, treatment guidance and post-treatment assessment of coronary artery diseases. By cannulating a miniature ultrasound transducer mounted catheter into an artery, the vessel lumen opening, vessel wall morphology and other associated blood and vessel properties can be precisely assessed in IVUS imaging. Ultrasound transducer, as the key component of an IVUS system, is critical in determining the IVUS imaging performance. In recent years, a wide range of achievements in ultrasound transducers have been reported for IVUS imaging applications. Herein, a comprehensive review is given on recent advances in ultrasound transducers for IVUS imaging. Firstly, a fundamental understanding of IVUS imaging principle, evaluation parameters and IVUS catheter are summarized. Secondly, three different types of ultrasound transducers (piezoelectric ultrasound transducer, piezoelectric micromachined ultrasound transducer and capacitive micromachined ultrasound transducer) for IVUS imaging are presented. Particularly, the recent advances in piezoelectric ultrasound transducer for IVUS imaging are extensively examined according to their different working mechanisms, configurations and materials adopted. Thirdly, IVUS-based multimodality intravascular imaging of atherosclerotic plaque is discussed. Finally, summary and perspectives on the future studies are highlighted for IVUS imaging applications. Full article

(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)

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22 pages, 11026 KiB

Open AccessReview

MoS₂ Based Photodetectors: A Review

by Alberto Taffelli, Sandra Dirè, Alberto Quaranta and Lucio Pancheri

Sensors 2021, 21(8), 2758; https://doi.org/10.3390/s21082758 - 14 Apr 2021

Cited by 144 | Viewed by 17405

Abstract

Photodetectors based on transition metal dichalcogenides (TMDs) have been widely reported in the literature and molybdenum disulfide (MoS₂) has been the most extensively explored for photodetection applications. The properties of MoS₂, such as direct band gap transition in low [...] Read more.

Photodetectors based on transition metal dichalcogenides (TMDs) have been widely reported in the literature and molybdenum disulfide (MoS₂) has been the most extensively explored for photodetection applications. The properties of MoS₂, such as direct band gap transition in low dimensional structures, strong light–matter interaction and good carrier mobility, combined with the possibility of fabricating thin MoS₂ films, have attracted interest for this material in the field of optoelectronics. In this work, MoS2-based photodetectors are reviewed in terms of their main performance metrics, namely responsivity, detectivity, response time and dark current. Although neat MoS2-based detectors already show remarkable characteristics in the visible spectral range, MoS₂ can be advantageously coupled with other materials to further improve the detector performance Nanoparticles (NPs) and quantum dots (QDs) have been exploited in combination with MoS₂ to boost the response of the devices in the near ultraviolet (NUV) and infrared (IR) spectral range. Moreover, heterostructures with different materials (e.g., other TMDs, Graphene) can speed up the response of the photodetectors through the creation of built-in electric fields and the faster transport of charge carriers. Finally, in order to enhance the stability of the devices, perovskites have been exploited both as passivation layers and as electron reservoirs. Full article

(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)

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25 pages, 1897 KiB

Open AccessReview

Wearable Sensors in Sports for Persons with Disability: A Systematic Review

by Lorenzo Rum, Oscar Sten, Eleonora Vendrame, Valeria Belluscio, Valentina Camomilla, Giuseppe Vannozzi, Luigi Truppa, Marco Notarantonio, Tommaso Sciarra, Aldo Lazich, Andrea Mannini and Elena Bergamini

Sensors 2021, 21(5), 1858; https://doi.org/10.3390/s21051858 - 7 Mar 2021

Cited by 56 | Viewed by 12369

Abstract

The interest and competitiveness in sports for persons with disabilities has increased significantly in the recent years, creating a demand for technological tools supporting practice. Wearable sensors offer non-invasive, portable and overall convenient ways to monitor sports practice. This systematic review aims at [...] Read more.

The interest and competitiveness in sports for persons with disabilities has increased significantly in the recent years, creating a demand for technological tools supporting practice. Wearable sensors offer non-invasive, portable and overall convenient ways to monitor sports practice. This systematic review aims at providing current evidence on the application of wearable sensors in sports for persons with disability. A search for articles published in English before May 2020 was performed on Scopus, Web-Of-Science, PubMed and EBSCO databases, searching titles, abstracts and keywords with a search string involving terms regarding wearable sensors, sports and disability. After full paper screening, 39 studies were included. Inertial and EMG sensors were the most commonly adopted wearable technologies, while wheelchair sports were the most investigated. Four main target applications of wearable sensors relevant to sports for people with disability were identified and discussed: athlete classification, injury prevention, performance characterization for training optimization and equipment customization. The collected evidence provides an overview on the application of wearable sensors in sports for persons with disability, providing useful indication for researchers, coaches and trainers. Several gaps in the different target applications are highlighted altogether with recommendation on future directions. Full article

(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)

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27 pages, 7493 KiB

Open AccessReview

Planar Phase-Variation Microwave Sensors for Material Characterization: A Review and Comparison of Various Approaches

by Jonathan Muñoz-Enano, Jan Coromina, Paris Vélez, Lijuan Su, Marta Gil, Pau Casacuberta and Ferran Martín

Sensors 2021, 21(4), 1542; https://doi.org/10.3390/s21041542 - 23 Feb 2021

Cited by 30 | Viewed by 4873

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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27 pages, 1120 KiB

Open AccessReview

Sensors and Measurements for Unmanned Systems: An Overview

by Eulalia Balestrieri, Pasquale Daponte, Luca De Vito and Francesco Lamonaca

Sensors 2021, 21(4), 1518; https://doi.org/10.3390/s21041518 - 22 Feb 2021

Cited by 105 | Viewed by 15000

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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21 pages, 5147 KiB

Open AccessReview

Magnetic Microwires with Unique Combination of Magnetic Properties Suitable for Various Magnetic Sensor Applications

by Paula Corte-Leon, Valentina Zhukova, Alexandr Chizhik, Juan Maria Blanco, Mihail Ipatov, Lorena Gonzalez-Legarreta and Arcady Zhukov

Sensors 2020, 20(24), 7203; https://doi.org/10.3390/s20247203 - 16 Dec 2020

Cited by 24 | Viewed by 4141

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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32 pages, 5105 KiB

Open AccessReview

Wavefront Shaping Concepts for Application in Optical Coherence Tomography—A Review

by Jonas Kanngiesser and Bernhard Roth

Sensors 2020, 20(24), 7044; https://doi.org/10.3390/s20247044 - 9 Dec 2020

Cited by 10 | Viewed by 5803

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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35 pages, 8857 KiB

Open AccessReview

Fundamental Concepts and Evolution of Wi-Fi User Localization: An Overview Based on Different Case Studies

by Guenther Retscher

Sensors 2020, 20(18), 5121; https://doi.org/10.3390/s20185121 - 8 Sep 2020

Cited by 21 | Viewed by 7128

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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36 pages, 10030 KiB

Open AccessEditor’s ChoiceReview

Micromachined Accelerometers with Sub-µg/√Hz Noise Floor: A Review

by Chen Wang, Fang Chen, Yuan Wang, Sina Sadeghpour, Chenxi Wang, Mathieu Baijot, Rui Esteves, Chun Zhao, Jian Bai, Huafeng Liu and Michael Kraft

Sensors 2020, 20(14), 4054; https://doi.org/10.3390/s20144054 - 21 Jul 2020

Cited by 78 | Viewed by 13583

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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14 pages, 1162 KiB

Open AccessPerspective

Noise as Diagnostic Tool for Quality and Reliability of MEMS

by Faisal Mohd-Yasin and David J. Nagel

Sensors 2021, 21(4), 1510; https://doi.org/10.3390/s21041510 - 22 Feb 2021

Cited by 6 | Viewed by 4159

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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