Sensors

215 KiB

Open AccessCorrection

Correction: Rozenstein, O., et al. Derivation of Land Surface Temperature for Landsat-8 TIRS Using a Split Window Algorithm. Sensors 2014, 14, 5768–5780

by Offer Rozenstein, Zhihao Qin, Yevgeny Derimian and Arnon Karnieli

Sensors 2014, 14(6), 11277; https://doi.org/10.3390/s140611277 - 24 Jun 2014

Cited by 7 | Viewed by 5387

Abstract

We have recently been made aware by a reader of a typo in Equation (4a) of our recent paper [1]. [...] Full article

(This article belongs to the Section Remote Sensors)

1458 KiB

Open AccessArticle

Implementation of Ultrasonic Sensing for High Resolution Measurement of Binary Gas Mixture Fractions

by Richard Bates, Michele Battistin, Stephane Berry, Alexander Bitadze, Pierre Bonneau, Nicolas Bousson, George Boyd, Gennaro Bozza, Olivier Crespo-Lopez, Enrico Da Riva, Cyril Degeorge, Cecile Deterre, Beniamino DiGirolamo, Martin Doubek, Gilles Favre, Jan Godlewski, Gregory Hallewell, Ahmed Hasib, Sergey Katunin, Nicolas Langevin, Didier Lombard, Michel Mathieu, Stephen McMahon, Koichi Nagai, Benjamin Pearson, David Robinson, Cecilia Rossi, Alexandre Rozanov, Michael Strauss, Michal Vitek, Vaclav Vacek and Lukasz Zwalinski Show full author list Hide full author list

Sensors 2014, 14(6), 11260-11276; https://doi.org/10.3390/s140611260 - 24 Jun 2014

Cited by 16 | Viewed by 11649

Abstract

We describe an ultrasonic instrument for continuous real-time analysis of the fractional mixture of a binary gas system. The instrument is particularly well suited to measurement of leaks of a high molecular weight gas into a system that is nominally composed of a [...] Read more.

We describe an ultrasonic instrument for continuous real-time analysis of the fractional mixture of a binary gas system. The instrument is particularly well suited to measurement of leaks of a high molecular weight gas into a system that is nominally composed of a single gas. Sensitivity < 5 × 10⁻⁵ is demonstrated to leaks of octaflouropropane (C₃F₈) coolant into nitrogen during a long duration (18 month) continuous study. The sensitivity of the described measurement system is shown to depend on the difference in molecular masses of the two gases in the mixture. The impact of temperature and pressure variances on the accuracy of the measurement is analysed. Practical considerations for the implementation and deployment of long term, in situ ultrasonic leak detection systems are also described. Although development of the described systems was motivated by the requirements of an evaporative fluorocarbon cooling system, the instrument is applicable to the detection of leaks of many other gases and to processes requiring continuous knowledge of particular binary gas mixture fractions. Full article

(This article belongs to the Special Issue Sensors for Fluid Leak Detection)

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Open AccessArticle

Robust Pedestrian Tracking and Recognition from FLIR Video: A Unified Approach via Sparse Coding

by Xin Li, Rui Guo and Chao Chen

Sensors 2014, 14(6), 11245-11259; https://doi.org/10.3390/s140611245 - 24 Jun 2014

Cited by 19 | Viewed by 7519

Abstract

Sparse coding is an emerging method that has been successfully applied to both robust object tracking and recognition in the vision literature. In this paper, we propose to explore a sparse coding-based approach toward joint object tracking-and-recognition and explore its potential in the [...] Read more.

Sparse coding is an emerging method that has been successfully applied to both robust object tracking and recognition in the vision literature. In this paper, we propose to explore a sparse coding-based approach toward joint object tracking-and-recognition and explore its potential in the analysis of forward-looking infrared (FLIR) video to support nighttime machine vision systems. A key technical contribution of this work is to unify existing sparse coding-based approaches toward tracking and recognition under the same framework, so that they can benefit from each other in a closed-loop. On the one hand, tracking the same object through temporal frames allows us to achieve improved recognition performance through dynamical updating of template/dictionary and combining multiple recognition results; on the other hand, the recognition of individual objects facilitates the tracking of multiple objects (i.e., walking pedestrians), especially in the presence of occlusion within a crowded environment. We report experimental results on both the CASIAPedestrian Database and our own collected FLIR video database to demonstrate the effectiveness of the proposed joint tracking-and-recognition approach. Full article

(This article belongs to the Special Issue Detection and Tracking of Targets in Forward-Looking InfraRed (FLIR) Imagery)

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Open AccessReview

Bacteria Inside Semiconductors as Potential Sensor Elements: Biochip Progress

by Vasu R. Sah and Robert E. Baier

Sensors 2014, 14(6), 11225-11244; https://doi.org/10.3390/s140611225 - 24 Jun 2014

Cited by 6 | Viewed by 9338

Abstract

It was discovered at the beginning of this Century that living bacteria—and specifically the extremophile Pseudomonas syzgii—could be captured inside growing crystals of pure water-corroding semiconductors—specifically germanium—and thereby initiated pursuit of truly functional “biochip-based” biosensors. This observation was first made at the [...] Read more.

It was discovered at the beginning of this Century that living bacteria—and specifically the extremophile Pseudomonas syzgii—could be captured inside growing crystals of pure water-corroding semiconductors—specifically germanium—and thereby initiated pursuit of truly functional “biochip-based” biosensors. This observation was first made at the inside ultraviolet-illuminated walls of ultrapure water-flowing semiconductor fabrication facilities (fabs) and has since been, not as perfectly, replicated in simpler flow cell systems for chip manufacture, described here. Recognizing the potential importance of these adducts as optical switches, for example, or probes of metabolic events, the influences of the fabs and their components on the crystal nucleation and growth phenomena now identified are reviewed and discussed with regard to further research needs. For example, optical beams of current photonic circuits can be more easily modulated by integral embedded cells into electrical signals on semiconductors. Such research responds to a recently published Grand Challenge in ceramic science, designing and synthesizing oxide electronics, surfaces, interfaces and nanoscale structures that can be tuned by biological stimuli, to reveal phenomena not otherwise possible with conventional semiconductor electronics. This short review addresses only the fabrication facilities’ features at the time of first production of these potential biochips. Full article

(This article belongs to the Special Issue On-Chip Sensors)

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Open AccessArticle

A Medical Cloud-Based Platform for Respiration Rate Measurement and Hierarchical Classification of Breath Disorders

by Atena Roshan Fekr, Majid Janidarmian, Katarzyna Radecka and Zeljko Zilic

Sensors 2014, 14(6), 11204-11224; https://doi.org/10.3390/s140611204 - 24 Jun 2014

Cited by 57 | Viewed by 12918

Abstract

The measurement of human respiratory signals is crucial in cyberbiological systems. A disordered breathing pattern can be the first symptom of different physiological, mechanical, or psychological dysfunctions. Therefore, a real-time monitoring of the respiration patterns, as well as respiration rate is a critical [...] Read more.

The measurement of human respiratory signals is crucial in cyberbiological systems. A disordered breathing pattern can be the first symptom of different physiological, mechanical, or psychological dysfunctions. Therefore, a real-time monitoring of the respiration patterns, as well as respiration rate is a critical need in medical applications. There are several methods for respiration rate measurement. However, despite their accuracy, these methods are expensive and could not be integrated in a body sensor network. In this work, we present a real-time cloud-based platform for both monitoring the respiration rate and breath pattern classification, remotely. The proposed system is designed particularly for patients with breathing problems (e.g., respiratory complications after surgery) or sleep disorders. Our system includes calibrated accelerometer sensor, Bluetooth Low Energy (BLE) and cloud-computing model. We also suggest a procedure to improve the accuracy of respiration rate for patients at rest positions. The overall error in the respiration rate calculation is obtained 0.53% considering SPR-BTA spirometer as the reference. Five types of respiration disorders, Bradapnea, Tachypnea, Cheyn-stokes, Kaussmal, and Biot’s breathing are classified based on hierarchical Support Vector Machine (SVM) with seven different features. We have evaluated the performance of the proposed classification while it is individualized to every subject (case 1) as well as considering all subjects (case 2). Since the selection of kernel function is a key factor to decide SVM’s performance, in this paper three different kernel functions are evaluated. The experiments are conducted with 11 subjects and the average accuracy of 94.52% for case 1 and the accuracy of 81.29% for case 2 are achieved based on Radial Basis Function (RBF). Finally, a performance evaluation has been done for normal and impaired subjects considering sensitivity, specificity and G-mean parameters of different kernel functions. Full article

(This article belongs to the Special Issue State-of-the-Art Sensors in Canada 2014)

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Graphical abstract

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Open AccessArticle

Smart Sensors Enable Smart Air Conditioning Control

by Chin-Chi Cheng and Dasheng Lee

Sensors 2014, 14(6), 11179-11203; https://doi.org/10.3390/s140611179 - 24 Jun 2014

Cited by 61 | Viewed by 31689

Abstract

In this study, mobile phones, wearable devices, temperature and human motion detectors are integrated as smart sensors for enabling smart air conditioning control. Smart sensors obtain feedback, especially occupants’ information, from mobile phones and wearable devices placed on human body. The information can [...] Read more.

In this study, mobile phones, wearable devices, temperature and human motion detectors are integrated as smart sensors for enabling smart air conditioning control. Smart sensors obtain feedback, especially occupants’ information, from mobile phones and wearable devices placed on human body. The information can be used to adjust air conditioners in advance according to humans’ intentions, in so-called intention causing control. Experimental results show that the indoor temperature can be controlled accurately with errors of less than ±0.1 °C. Rapid cool down can be achieved within 2 min to the optimized indoor capacity after occupants enter a room. It’s also noted that within two-hour operation the total compressor output of the smart air conditioner is 48.4% less than that of the one using On-Off control. The smart air conditioner with wearable devices could detect the human temperature and activity during sleep to determine the sleeping state and adjusting the sleeping function flexibly. The sleeping function optimized by the smart air conditioner with wearable devices could reduce the energy consumption up to 46.9% and keep the human health. The presented smart air conditioner could provide a comfortable environment and achieve the goals of energy conservation and environmental protection. Full article

(This article belongs to the Section Physical Sensors)

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Open AccessArticle

Enhancing Evacuation Plans with a Situation Awareness System Based on End-User Knowledge Provision

by Augusto Morales, Ramon Alcarria, Diego Martin and Tomas Robles

Sensors 2014, 14(6), 11153-11178; https://doi.org/10.3390/s140611153 - 24 Jun 2014

Cited by 26 | Viewed by 9845

Abstract

Recent disasters have shown that having clearly defined preventive procedures and decisions is a critical component that minimizes evacuation hazards and ensures a rapid and successful evolution of evacuation plans. In this context, we present our Situation-Aware System for enhancing Evacuation Plans (SASEP) [...] Read more.

Recent disasters have shown that having clearly defined preventive procedures and decisions is a critical component that minimizes evacuation hazards and ensures a rapid and successful evolution of evacuation plans. In this context, we present our Situation-Aware System for enhancing Evacuation Plans (SASEP) system, which allows creating end-user business rules that technically support the specific events, conditions and actions related to evacuation plans. An experimental validation was carried out where 32 people faced a simulated emergency situation, 16 of them using SASEP and the other 16 using a legacy system based on static signs. From the results obtained, we compare both techniques and discuss in which situations SASEP offers a better evacuation route option, confirming that it is highly valuable when there is a threat in the evacuation route. In addition, a study about user satisfaction using both systems is presented showing in which cases the systems are assessed as satisfactory, relevant and not frustrating. Full article

(This article belongs to the Section Sensor Networks)

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Graphical abstract

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Open AccessArticle

Proximal Sensing of Plant-Pathogen Interactions in Spring Barley with Three Fluorescence Techniques

by Georg Leufen, Georg Noga and Mauricio Hunsche

Sensors 2014, 14(6), 11135-11152; https://doi.org/10.3390/s140611135 - 24 Jun 2014

Cited by 12 | Viewed by 7270

Abstract

In the last years fluorescence spectroscopy has come to be viewed as an essential approach in key research fields of applied plant sciences. However, the quantity and particularly the quality of information produced by different equipment might vary considerably. In this study we [...] Read more.

In the last years fluorescence spectroscopy has come to be viewed as an essential approach in key research fields of applied plant sciences. However, the quantity and particularly the quality of information produced by different equipment might vary considerably. In this study we investigate the potential of three optical devices for the proximal sensing of plant-pathogen interactions in four genotypes of spring barley. For this purpose, the fluorescence lifetime, the image-resolved multispectral fluorescence and selected indices of a portable multiparametric fluorescence device were recorded at 3, 6, and 9 days after inoculation (dai) from healthy leaves as well as from leaves inoculated with powdery mildew (Blumeria graminis) or leaf rust (Puccinia hordei). Genotype-specific responses to pathogen infections were revealed already at 3 dai by higher fluorescence mean lifetimes in the spectral range from 410 to 560 nm in the less susceptible varieties. Noticeable pathogen-induced modifications were also revealed by the ‘Blue-to-Far-Red Fluorescence Ratio’ and the ‘Simple Fluorescence Ratio’. Particularly in the susceptible varieties the differences became more evident in the time-course of the experiment i.e., following the pathogen development. The relevance of the blue and green fluorescence to exploit the plant-pathogen interaction was demonstrated by the multispectral fluorescence imaging system. As shown, mildewed leaves were characterized by exceptionally high blue fluorescence, contrasting the values observed in rust inoculated leaves. Further, we confirm that the intensity of green fluorescence depends on the pathogen infection and the stage of disease development; this information might allow a differentiation of both diseases. Moreover, our results demonstrate that the detection area might influence the quality of the information, although it had a minor impact only in the current study. Finally, we highlight the relevance of different excitation-emission channels to better understand and evaluate plant-physiological alterations due to pathogen infections. Full article

(This article belongs to the Section Biosensors)

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Open AccessArticle

Context Graphs as an Efficient and User-Friendly Method of Describing and Recognizing a Situation in AAL

by Andrei Olaru and Adina Magda Florea

Sensors 2014, 14(6), 11110-11134; https://doi.org/10.3390/s140611110 - 23 Jun 2014

Cited by 4 | Viewed by 6085

Abstract

In the field of ambient assisted living, the best results are achieved with systems that are less intrusive and more intelligent, that can easily integrate both formal and informal caregivers and that can easily adapt to the changes in the situation of the [...] Read more.

In the field of ambient assisted living, the best results are achieved with systems that are less intrusive and more intelligent, that can easily integrate both formal and informal caregivers and that can easily adapt to the changes in the situation of the elderly or disabled person. This paper presents a graph-based representation for context information and a simple and intuitive method for situation recognition. Both the input and the results are easy to visualize, understand and use. Experiments have been performed on several AAL-specific scenarios. Full article

(This article belongs to the Special Issue Ambient Assisted Living (AAL): Sensors, Architectures and Applications)

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Open AccessArticle

A Doped Polyaniline Modified Electrode Amperometric Biosensor for Gluconic Acid Determination in Grapes

by Donatella Albanese, Francesca Malvano, Adriana Sannini, Roberto Pilloton and Marisa Di Matteo

Sensors 2014, 14(6), 11097-11109; https://doi.org/10.3390/s140611097 - 23 Jun 2014

Cited by 14 | Viewed by 7100

Abstract

In winemaking gluconic acid is an important marker for quantitative evaluation of grape infection by Botrytis cinerea. A screen-printed amperometric bienzymatic sensor for the determination of gluconic acid based on gluconate kinase (GK) and 6-phospho-D-gluconate dehydrogenase (6PGDH) coimmobilized onto polyaniline/poly (2-acrylamido-2-methyl-1-propanesulfonic acid; [...] Read more.

In winemaking gluconic acid is an important marker for quantitative evaluation of grape infection by Botrytis cinerea. A screen-printed amperometric bienzymatic sensor for the determination of gluconic acid based on gluconate kinase (GK) and 6-phospho-D-gluconate dehydrogenase (6PGDH) coimmobilized onto polyaniline/poly (2-acrylamido-2-methyl-1-propanesulfonic acid; PANI-PAAMPSA) is reported in this study. The conductive polymer electrodeposed on the working electrode surface allowed the detection of NADH at low potential (0.1 V) with a linear range from 4 × 10⁻³ to 1 mM (R² = 0.99) and a sensitivity of 419.44 nA∙mM⁻¹. The bienzymatic sensor has been optimized with regard to GK/6PGDH enzymatic unit ratio and ATP/NADP⁺ molar ratio which resulted equal to 0.33 and 1.2, respectively. Under these conditions a sensitivity of 255.2 nA∙mM⁻¹, a limit of detection of 5 μM and a Relative Standard Deviation (RSD) of 4.2% (n = 5) have been observed. Finally, the biosensor has been applied for gluconic acid measurements in must grape samples and the matrix effect has been taken into consideration. The results have been compared with those obtained on the same samples with a commercial kit based on a spectrophotometric enzyme assay and were in good agreement, showing the capability of the bienzymatic PANI-PAAMPSA biosensor for gluconic acid measurements and thus for the evaluation of Botrytis cinerea infection in grapes. Full article

(This article belongs to the Special Issue Amperometric Biosensors)

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Open AccessArticle

A Model-Based Approach for Bridging Virtual and Physical Sensor Nodes in a Hybrid Simulation Framework

by Mohammad Mozumdar, Zhen Yu Song, Luciano Lavagno and Alberto L. Sangiovanni-Vincentelli

Sensors 2014, 14(6), 11070-11096; https://doi.org/10.3390/s140611070 - 23 Jun 2014

Cited by 7 | Viewed by 7256

Abstract

The Model Based Design (MBD) approach is a popular trend to speed up application development of embedded systems, which uses high-level abstractions to capture functional requirements in an executable manner, and which automates implementation code generation. Wireless Sensor Networks (WSNs) are an emerging [...] Read more.

The Model Based Design (MBD) approach is a popular trend to speed up application development of embedded systems, which uses high-level abstractions to capture functional requirements in an executable manner, and which automates implementation code generation. Wireless Sensor Networks (WSNs) are an emerging very promising application area for embedded systems. However, there is a lack of tools in this area, which would allow an application developer to model a WSN application by using high level abstractions, simulate it mapped to a multi-node scenario for functional analysis, and finally use the refined model to automatically generate code for different WSN platforms. Motivated by this idea, in this paper we present a hybrid simulation framework that not only follows the MBD approach for WSN application development, but also interconnects a simulated sub-network with a physical sub-network and then allows one to co-simulate them, which is also known as Hardware-In-the-Loop (HIL) simulation. Full article

(This article belongs to the Special Issue Wireless Sensor Networks and the Internet of Things)

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Open AccessArticle

Spike Detection Based on Normalized Correlation with Automatic Template Generation

by Wen-Jyi Hwang, Szu-Huai Wang and Ya-Tzu Hsu

Sensors 2014, 14(6), 11049-11069; https://doi.org/10.3390/s140611049 - 23 Jun 2014

Cited by 7 | Viewed by 6841

Abstract

A novel feedback-based spike detection algorithm for noisy spike trains is presented in this paper. It uses the information extracted from the results of spike classification for the enhancement of spike detection. The algorithm performs template matching for spike detection by a normalized [...] Read more.

A novel feedback-based spike detection algorithm for noisy spike trains is presented in this paper. It uses the information extracted from the results of spike classification for the enhancement of spike detection. The algorithm performs template matching for spike detection by a normalized correlator. The detected spikes are then sorted by the OSortalgorithm. The mean of spikes of each cluster produced by the OSort algorithm is used as the template of the normalized correlator for subsequent detection. The automatic generation and updating of templates enhance the robustness of the spike detection to input trains with various spike waveforms and noise levels. Experimental results show that the proposed algorithm operating in conjunction with OSort is an efficient design for attaining high detection and classification accuracy for spike sorting. Full article

(This article belongs to the Section Physical Sensors)

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Open AccessEditorial

Introduction to the Special Issue on “State-of-the-Art Sensor Technology in Japan 2012”

by Kouji Harada and Yoshiteru Ishida

Sensors 2014, 14(6), 11045-11048; https://doi.org/10.3390/s140611045 - 23 Jun 2014

Cited by 3 | Viewed by 5183

Abstract

Since the previous special issue: State-of-the-Art Sensor Technology in Japan in 2008, which collected papers on sensing technology for monitoring of humans and the environment, we have experienced the Great East Japan Earthquake, Tsunami on 11 March 2011. This special issue, while aiming [...] Read more.

Since the previous special issue: State-of-the-Art Sensor Technology in Japan in 2008, which collected papers on sensing technology for monitoring of humans and the environment, we have experienced the Great East Japan Earthquake, Tsunami on 11 March 2011. This special issue, while aiming in the same direction, focuses on technologies for: (1) accuracy and sensitivity, (2) wireless functions, (3) real-time response, (4) portability (miniaturization), and (5) privacy preservation to promote sensor and sensing technologies for disaster prevention and resilient systems. [...] Full article

(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Japan 2012)

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Open AccessArticle

A Mobile Device System for Early Warning of ECG Anomalies

by Adam Szczepański and Khalid Saeed

Sensors 2014, 14(6), 11031-11044; https://doi.org/10.3390/s140611031 - 20 Jun 2014

Cited by 29 | Viewed by 18929

Abstract

With the rapid increase in computational power of mobile devices the amount of ambient intelligence-based smart environment systems has increased greatly in recent years. A proposition of such a solution is described in this paper, namely real time monitoring of an electrocardiogram (ECG) [...] Read more.

With the rapid increase in computational power of mobile devices the amount of ambient intelligence-based smart environment systems has increased greatly in recent years. A proposition of such a solution is described in this paper, namely real time monitoring of an electrocardiogram (ECG) signal during everyday activities for identification of life threatening situations. The paper, being both research and review, describes previous work of the authors, current state of the art in the context of the authors’ work and the proposed aforementioned system. Although parts of the solution were described in earlier publications of the authors, the whole concept is presented completely for the first time along with the prototype implementation on mobile device—a Windows 8 tablet with Modern UI. The system has three main purposes. The first goal is the detection of sudden rapid cardiac malfunctions and informing the people in the patient’s surroundings, family and friends and the nearest emergency station about the deteriorating health of the monitored person. The second goal is a monitoring of ECG signals under non-clinical conditions to detect anomalies that are typically not found during diagnostic tests. The third goal is to register and analyze repeatable, long-term disturbances in the regular signal and finding their patterns. Full article

(This article belongs to the Special Issue Ambient Assisted Living (AAL): Sensors, Architectures and Applications)

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Open AccessCommunication

Array Formatting of the Heat-Transfer Method (HTM) for the Detection of Small Organic Molecules by Molecularly Imprinted Polymers

by Gideon Wackers, Thijs Vandenryt, Peter Cornelis, Evelien Kellens, Ronald Thoelen, Ward De Ceuninck, Patricia Losada-Pérez, Bart Van Grinsven, Marloes Peeters and Patrick Wagner

Sensors 2014, 14(6), 11016-11030; https://doi.org/10.3390/s140611016 - 20 Jun 2014

Cited by 23 | Viewed by 9020

Abstract

In this work we present the first steps towards a molecularly imprinted polymer (MIP)-based biomimetic sensor array for the detection of small organic molecules via the heat-transfer method (HTM). HTM relies on the change in thermal resistance upon binding of the target molecule [...] Read more.

In this work we present the first steps towards a molecularly imprinted polymer (MIP)-based biomimetic sensor array for the detection of small organic molecules via the heat-transfer method (HTM). HTM relies on the change in thermal resistance upon binding of the target molecule to the MIP-type receptor. A flow-through sensor cell was developed, which is segmented into four quadrants with a volume of 2.5 μL each, allowing four measurements to be done simultaneously on a single substrate. Verification measurements were conducted, in which all quadrants received a uniform treatment and all four channels exhibited a similar response. Subsequently, measurements were performed in quadrants, which were functionalized with different MIP particles. Each of these quadrants was exposed to the same buffer solution, spiked with different molecules, according to the MIP under analysis. With the flow cell design we could discriminate between similar small organic molecules and observed no significant cross-selectivity. Therefore, the MIP array sensor platform with HTM as a readout technique, has the potential to become a low-cost analysis tool for bioanalytical applications. Full article

(This article belongs to the Special Issue Biomimetic Receptors and Sensors)

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Graphical abstract

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Open AccessArticle

Magnetic Field Feature Extraction and Selection for Indoor Location Estimation

by Carlos E. Galván-Tejada, Juan Pablo García-Vázquez and Ramon F. Brena

Sensors 2014, 14(6), 11001-11015; https://doi.org/10.3390/s140611001 - 20 Jun 2014

Cited by 56 | Viewed by 8543

Abstract

User indoor positioning has been under constant improvement especially with the availability of new sensors integrated into the modern mobile devices, which allows us to exploit not only infrastructures made for everyday use, such as WiFi, but also natural infrastructure, as is the [...] Read more.

User indoor positioning has been under constant improvement especially with the availability of new sensors integrated into the modern mobile devices, which allows us to exploit not only infrastructures made for everyday use, such as WiFi, but also natural infrastructure, as is the case of natural magnetic field. In this paper we present an extension and improvement of our current indoor localization model based on the feature extraction of 46 magnetic field signal features. The extension adds a feature selection phase to our methodology, which is performed through Genetic Algorithm (GA) with the aim of optimizing the fitness of our current model. In addition, we present an evaluation of the final model in two different scenarios: home and office building. The results indicate that performing a feature selection process allows us to reduce the number of signal features of the model from 46 to 5 regardless the scenario and room location distribution. Further, we verified that reducing the number of features increases the probability of our estimator correctly detecting the user’s location (sensitivity) and its capacity to detect false positives (specificity) in both scenarios. Full article

(This article belongs to the Special Issue Select Papers from UCAmI & IWAAL 2013 - the 7th International Conference on Ubiquitous Computing and Ambient Intelligence & the 5th International Workshop on Ambient Assisted Living (UCAmI & IWAAL 2013: Pervasive Sensing Solutions)

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Open AccessReview

Frequency-Shifted Interferometry — A Versatile Fiber-Optic Sensing Technique

by Fei Ye, Yiwei Zhang, Bing Qi and Li Qian

Sensors 2014, 14(6), 10977-11000; https://doi.org/10.3390/s140610977 - 20 Jun 2014

Cited by 16 | Viewed by 7998

Abstract

Fiber-optic sensing is a field that is developing at a fast pace. Novel fiber-optic sensor designs and sensing principles constantly open doors for new opportunities. In this paper, we review a fiber-optic sensing technique developed in our research group called frequency-shifted interferometry (FSI). [...] Read more.

Fiber-optic sensing is a field that is developing at a fast pace. Novel fiber-optic sensor designs and sensing principles constantly open doors for new opportunities. In this paper, we review a fiber-optic sensing technique developed in our research group called frequency-shifted interferometry (FSI). This technique uses a continuous-wave light source, an optical frequency shifter, and a slow detector. We discuss the operation principles of several FSI implementations and show their applications in fiber length and dispersion measurement, locating weak reflections along a fiber link, fiber-optic sensor multiplexing, and high-sensitivity cavity ring-down measurement. Detailed analysis of FSI system parameters is also presented. Full article

(This article belongs to the Special Issue State-of-the-Art Sensors in Canada 2014)

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Open AccessArticle

Computational Intelligence Techniques for Tactile Sensing Systems

by Paolo Gastaldo, Luigi Pinna, Lucia Seminara, Maurizio Valle and Rodolfo Zunino

Sensors 2014, 14(6), 10952-10976; https://doi.org/10.3390/s140610952 - 19 Jun 2014

Cited by 29 | Viewed by 8210

Abstract

Tactile sensing helps robots interact with humans and objects effectively in real environments. Piezoelectric polymer sensors provide the functional building blocks of the robotic electronic skin, mainly thanks to their flexibility and suitability for detecting dynamic contact events and for recognizing the touch [...] Read more.

Tactile sensing helps robots interact with humans and objects effectively in real environments. Piezoelectric polymer sensors provide the functional building blocks of the robotic electronic skin, mainly thanks to their flexibility and suitability for detecting dynamic contact events and for recognizing the touch modality. The paper focuses on the ability of tactile sensing systems to support the challenging recognition of certain qualities/modalities of touch. The research applies novel computational intelligence techniques and a tensor-based approach for the classification of touch modalities; its main results consist in providing a procedure to enhance system generalization ability and architecture for multi-class recognition applications. An experimental campaign involving 70 participants using three different modalities in touching the upper surface of the sensor array was conducted, and confirmed the validity of the approach. Full article

(This article belongs to the Special Issue Tactile Sensors and Sensing Systems)

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Open AccessReview

Application of Wireless Power Transmission Systems in Wireless Capsule Endoscopy: An Overview

by Md Rubel Basar, Mohd Yazed Ahmad, Jongman Cho and Fatimah Ibrahim

Sensors 2014, 14(6), 10929-10951; https://doi.org/10.3390/s140610929 - 19 Jun 2014

Cited by 84 | Viewed by 14842

Abstract

Wireless capsule endoscopy (WCE) is a promising technology for direct diagnosis of the entire small bowel to detect lethal diseases, including cancer and obscure gastrointestinal bleeding (OGIB). To improve the quality of diagnosis, some vital specifications of WCE such as image resolution, frame [...] Read more.

Wireless capsule endoscopy (WCE) is a promising technology for direct diagnosis of the entire small bowel to detect lethal diseases, including cancer and obscure gastrointestinal bleeding (OGIB). To improve the quality of diagnosis, some vital specifications of WCE such as image resolution, frame rate and working time need to be improved. Additionally, future multi-functioning robotic capsule endoscopy (RCE) units may utilize advanced features such as active system control over capsule motion, drug delivery systems, semi-surgical tools and biopsy. However, the inclusion of the above advanced features demands additional power that make conventional power source methods impractical. In this regards, wireless power transmission (WPT) system has received attention among researchers to overcome this problem. Systematic reviews on techniques of using WPT for WCE are limited, especially when involving the recent technological advancements. This paper aims to fill that gap by providing a systematic review with emphasis on the aspects related to the amount of transmitted power, the power transmission efficiency, the system stability and patient safety. It is noted that, thus far the development of WPT system for this WCE application is still in initial stage and there is room for improvements, especially involving system efficiency, stability, and the patient safety aspects. Full article

(This article belongs to the Special Issue Biomedical Sensors and Systems)

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821 KiB

Open AccessReview

The Theory and Fundamentals of Bioimpedance Analysis in Clinical Status Monitoring and Diagnosis of Diseases

by Sami F. Khalil, Mas S. Mohktar and Fatimah Ibrahim

Sensors 2014, 14(6), 10895-10928; https://doi.org/10.3390/s140610895 - 19 Jun 2014

Cited by 444 | Viewed by 32475

Abstract

Bioimpedance analysis is a noninvasive, low cost and a commonly used approach for body composition measurements and assessment of clinical condition. There are a variety of methods applied for interpretation of measured bioimpedance data and a wide range of utilizations of bioimpedance in [...] Read more.

Bioimpedance analysis is a noninvasive, low cost and a commonly used approach for body composition measurements and assessment of clinical condition. There are a variety of methods applied for interpretation of measured bioimpedance data and a wide range of utilizations of bioimpedance in body composition estimation and evaluation of clinical status. This paper reviews the main concepts of bioimpedance measurement techniques including the frequency based, the allocation based, bioimpedance vector analysis and the real time bioimpedance analysis systems. Commonly used prediction equations for body composition assessment and influence of anthropometric measurements, gender, ethnic groups, postures, measurements protocols and electrode artifacts in estimated values are also discussed. In addition, this paper also contributes to the deliberations of bioimpedance analysis assessment of abnormal loss in lean body mass and unbalanced shift in body fluids and to the summary of diagnostic usage in different kinds of conditions such as cardiac, pulmonary, renal, and neural and infection diseases. Full article

(This article belongs to the Special Issue Biomedical Sensors and Systems)

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Open AccessArticle

Optical Characteristic Research on Fiber Bragg Gratings Utilizing Finite Element and Eigenmode Expansion Methods

by Yuejing He and Xuanyang Chen

Sensors 2014, 14(6), 10876-10894; https://doi.org/10.3390/s140610876 - 19 Jun 2014

Cited by 3 | Viewed by 5216

Abstract

Compared with coupled-mode theory (CMT), which is widely used for studies involving optical fiber Bragg gratings (FBGs), the proposed investigation scheme is visualized, diagrammatic, and simple. This method combines the finite element method (FEM) and eigenmode expansion method (EEM). The function of the [...] Read more.

Compared with coupled-mode theory (CMT), which is widely used for studies involving optical fiber Bragg gratings (FBGs), the proposed investigation scheme is visualized, diagrammatic, and simple. This method combines the finite element method (FEM) and eigenmode expansion method (EEM). The function of the FEM is to calculate all guided modes that match the boundary conditions of optical fiber waveguides. Moreover, the FEM is used for implementing power propagation for HE₁₁ in optical fiber devices. How the periodic characteristic of FBG causes this novel scheme to be substantially superior to CMT is explained in detail. Regarding current numerical calculation techniques, the scheme proposed in this paper is the only method capable of the 3D design and analysis of large periodic components. Additionally, unlike CMT, in which deviations exist between the designed wavelength λ_D and the maximal reflection wavelength λ_max, the proposed method performs rapid scans of the periods of optical FBG. Therefore, once the operating wavelength is set for the component design, the maximal reflection wavelength of the final products can be accurately limited to that of the original design, such as λ = 1550 nm. Furthermore, a comparison between the period scan plot and the optical spectra plot for FBG indicated an inverse relationship between the periods and wavelengths. Consequently, this property can be used to predict the final FBG spectra before implementing time-consuming calculations. By employing this novel investigation scheme involving a rigorous design procedure, the graphical and simple calculation method reduces the studying time and professional expertise required for researching and applying optical FBG. Full article

(This article belongs to the Section Physical Sensors)

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530 KiB

Open AccessArticle

A New Surface Plasmon Resonance-Based Immunoassay for Rapid, Reproducible and Sensitive Quantification of Pentraxin-3 in Human Plasma

by Mara Canovi, Jacopo Lucchetti, Matteo Stravalaci, Sonia Valentino, Barbara Bottazzi, Mario Salmona, Antonio Bastone and Marco Gobbi

Sensors 2014, 14(6), 10864-10875; https://doi.org/10.3390/s140610864 - 19 Jun 2014

Cited by 18 | Viewed by 7508

Abstract

A new immunoassay based on surface plasmon resonance (SPR) for the rapid, reproducible and sensitive determination of pentraxin-3 (PTX3) levels in human plasma has been developed and characterized. The method involves a 3-min flow of plasma over a sensor chip pre-coated with a [...] Read more.

A new immunoassay based on surface plasmon resonance (SPR) for the rapid, reproducible and sensitive determination of pentraxin-3 (PTX3) levels in human plasma has been developed and characterized. The method involves a 3-min flow of plasma over a sensor chip pre-coated with a monoclonal anti-PTX3 antibody (MNB4), followed by a 3-min flow of a polyclonal anti-PTX3 antibody (pAb), required for specific recognition of captured PTX3. The SPR signal generated with this secondary antibody linearly correlates with the plasma PTX3 concentration, in the range of 5–1500 ng/mL, with a lowest limit of detection of 5 ng/mL. The PTX3 concentrations determined with the SPR-based immunoassay in the plasma of 21 patients with sepsis, ranging 15–1600 ng/mL, were superimposable to those found in a classic ELISA immunoassay. Since the PTX3 concentration in the plasma of healthy subjects is <2 ng/mL, but markedly rises in certain medical conditions, the method is useful to quantify pathological levels of this important biomarker, with important diagnostic applications. In comparison with the classic ELISA, the SPR-based approach is much faster (30 min versus 4–5 h) and could be exploited for the development of new cost-effective SPR devices for point-of-care diagnosis. Full article

(This article belongs to the Special Issue Immunosensors 2014)

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Open AccessArticle

Isolation and Epitope Mapping of Staphylococcal Enterotoxin B Single-Domain Antibodies

by Kendrick B. Turner, Dan Zabetakis, Patricia Legler, Ellen R. Goldman and George P. Anderson

Sensors 2014, 14(6), 10846-10863; https://doi.org/10.3390/s140610846 - 19 Jun 2014

Cited by 11 | Viewed by 7405

Abstract

Single-domain antibodies (sdAbs), derived from the heavy chain only antibodies found in camelids such as llamas have the potential to provide rugged detection reagents with high affinities, and the ability to refold after denaturation. We have isolated and characterized sdAbs specific to staphylococcal [...] Read more.

Single-domain antibodies (sdAbs), derived from the heavy chain only antibodies found in camelids such as llamas have the potential to provide rugged detection reagents with high affinities, and the ability to refold after denaturation. We have isolated and characterized sdAbs specific to staphylococcal enterotoxin B (SEB) which bind to two distinct epitopes and are able to function in a sandwich immunoassay for toxin detection. Characterization of these sdAbs revealed that each exhibited nanomolar binding affinities or better. Melting temperatures for the sdAbs ranged from approximately 60 °C to over 70 °C, with each demonstrating at least partial refolding after denaturation and several were able to completely refold. A first set of sdAbs was isolated by panning the library using adsorbed antigen, all of which recognized the same epitope on SEB. Epitope mapping suggested that these sdAbs bind to a particular fragment of SEB (VKSIDQFLYFDLIYSI) containing position L45 (underlined), which is involved in binding to the major histocompatibility complex (MHC). Differences in the binding affinities of the sdAbs to SEB and a less-toxic vaccine immunogen, SEBv (L45R/Y89A/Y94A) were also consistent with binding to this epitope. A sandwich panning strategy was utilized to isolate sdAbs which bind a second epitope. This epitope differed from the initial one obtained or from that recognized by previously isolated anti-SEB sdAb A3. Using SEB-toxin spiked milk we demonstrated that these newly isolated sdAbs could be utilized in sandwich-assays with each other, A3, and with various monoclonal antibodies. Full article

(This article belongs to the Special Issue Chemo- and Biosensors for Security and Defense)

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393 KiB

Open AccessArticle

Detection and Tracking of a Moving Target Using SAR Images with the Particle Filter-Based Track-Before-Detect Algorithm

by Han Gao and Jingwen Li

Sensors 2014, 14(6), 10829-10845; https://doi.org/10.3390/s140610829 - 19 Jun 2014

Cited by 24 | Viewed by 6379

Abstract

A novel approach to detecting and tracking a moving target using synthetic aperture radar (SAR) images is proposed in this paper. Achieved with the particle filter (PF) based track-before-detect (TBD) algorithm, the approach is capable of detecting and tracking the low signal-to-noise ratio [...] Read more.

A novel approach to detecting and tracking a moving target using synthetic aperture radar (SAR) images is proposed in this paper. Achieved with the particle filter (PF) based track-before-detect (TBD) algorithm, the approach is capable of detecting and tracking the low signal-to-noise ratio (SNR) moving target with SAR systems, which the traditional track-after-detect (TAD) approach is inadequate for. By incorporating the signal model of the SAR moving target into the algorithm, the ambiguity in target azimuth position and radial velocity is resolved while tracking, which leads directly to the true estimation. With the sub-area substituted for the whole area to calculate the likelihood ratio and a pertinent choice of the number of particles, the computational efficiency is improved with little loss in the detection and tracking performance. The feasibility of the approach is validated and the performance is evaluated with Monte Carlo trials. It is demonstrated that the proposed approach is capable to detect and track a moving target with SNR as low as 7 dB, and outperforms the traditional TAD approach when the SNR is below 14 dB. Full article

(This article belongs to the Section Remote Sensors)

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955 KiB

Open AccessArticle

EPMOSt: An Energy-Efficient Passive Monitoring System for Wireless Sensor Networks

by Fernando P. Garcia, Rossana M. C. Andrade, Carina T. Oliveira and José Neuman De Souza

Sensors 2014, 14(6), 10804-10828; https://doi.org/10.3390/s140610804 - 19 Jun 2014

Cited by 22 | Viewed by 8987

Abstract

Monitoring systems are important for debugging and analyzing Wireless Sensor Networks (WSN). In passive monitoring, a monitoring network needs to be deployed in addition to the network to be monitored, named the target network. The monitoring network captures and analyzes packets transmitted by [...] Read more.

Monitoring systems are important for debugging and analyzing Wireless Sensor Networks (WSN). In passive monitoring, a monitoring network needs to be deployed in addition to the network to be monitored, named the target network. The monitoring network captures and analyzes packets transmitted by the target network. An energy-efficient passive monitoring system is necessary when we need to monitor a WSN in a real scenario because the lifetime of the monitoring network is extended and, consequently, the target network benefits from the monitoring for a longer time. In this work, we have identified, analyzed and compared the main passive monitoring systems proposed for WSN. During our research, we did not identify any passive monitoring system for WSN that aims to reduce the energy consumption of the monitoring network. Therefore, we propose an Energy-efficient Passive MOnitoring SysTem for WSN named EPMOSt that provides monitoring information using a Simple Network Management Protocol (SNMP) agent. Thus, any management tool that supports the SNMP protocol can be integrated with this monitoring system. Experiments with real sensors were performed in several scenarios. The results obtained show the energy efficiency of the proposed monitoring system and the viability of using it to monitor WSN in real scenarios. Full article

(This article belongs to the Section Sensor Networks)

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Open AccessArticle

Active Optical Sensors for Tree Stem Detection and Classification in Nurseries

by Miguel Garrido, Manuel Perez-Ruiz, Constantino Valero, Chris J. Gliever, Bradley D. Hanson and David C. Slaughter

Sensors 2014, 14(6), 10783-10803; https://doi.org/10.3390/s140610783 - 19 Jun 2014

Cited by 19 | Viewed by 8235

Abstract

Active optical sensing (LIDAR and light curtain transmission) devices mounted on a mobile platform can correctly detect, localize, and classify trees. To conduct an evaluation and comparison of the different sensors, an optical encoder wheel was used for vehicle odometry and provided a [...] Read more.

Active optical sensing (LIDAR and light curtain transmission) devices mounted on a mobile platform can correctly detect, localize, and classify trees. To conduct an evaluation and comparison of the different sensors, an optical encoder wheel was used for vehicle odometry and provided a measurement of the linear displacement of the prototype vehicle along a row of tree seedlings as a reference for each recorded sensor measurement. The field trials were conducted in a juvenile tree nursery with one-year-old grafted almond trees at Sierra Gold Nurseries, Yuba City, CA, United States. Through these tests and subsequent data processing, each sensor was individually evaluated to characterize their reliability, as well as their advantages and disadvantages for the proposed task. Test results indicated that 95.7% and 99.48% of the trees were successfully detected with the LIDAR and light curtain sensors, respectively. LIDAR correctly classified, between alive or dead tree states at a 93.75% success rate compared to 94.16% for the light curtain sensor. These results can help system designers select the most reliable sensor for the accurate detection and localization of each tree in a nursery, which might allow labor-intensive tasks, such as weeding, to be automated without damaging crops. Full article

(This article belongs to the Special Issue Agriculture and Forestry: Sensors, Technologies and Procedures)

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Open AccessArticle

Obstacle Classification and 3D Measurement in Unstructured Environments Based on ToF Cameras

by Hongshan Yu, Jiang Zhu, Yaonan Wang, Wenyan Jia, Mingui Sun and Yandong Tang

Sensors 2014, 14(6), 10753-10782; https://doi.org/10.3390/s140610753 - 18 Jun 2014

Cited by 25 | Viewed by 8988

Abstract

Inspired by the human 3D visual perception system, we present an obstacle detection and classification method based on the use of Time-of-Flight (ToF) cameras for robotic navigation in unstructured environments. The ToF camera provides 3D sensing by capturing an image along with per-pixel [...] Read more.

Inspired by the human 3D visual perception system, we present an obstacle detection and classification method based on the use of Time-of-Flight (ToF) cameras for robotic navigation in unstructured environments. The ToF camera provides 3D sensing by capturing an image along with per-pixel 3D space information. Based on this valuable feature and human knowledge of navigation, the proposed method first removes irrelevant regions which do not affect robot’s movement from the scene. In the second step, regions of interest are detected and clustered as possible obstacles using both 3D information and intensity image obtained by the ToF camera. Consequently, a multiple relevance vector machine (RVM) classifier is designed to classify obstacles into four possible classes based on the terrain traversability and geometrical features of the obstacles. Finally, experimental results in various unstructured environments are presented to verify the robustness and performance of the proposed approach. We have found that, compared with the existing obstacle recognition methods, the new approach is more accurate and efficient. Full article

(This article belongs to the Section Physical Sensors)

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1572 KiB

Open AccessArticle

A Ubiquitous Sensor Network Platform for Integrating Smart Devices into the Semantic Sensor Web

by David Díaz Pardo de Vera, Álvaro Sigüenza Izquierdo, Jesús Bernat Vercher and Luis Alfonso Hernández Gómez

Sensors 2014, 14(6), 10725-10752; https://doi.org/10.3390/s140610725 - 18 Jun 2014

Cited by 19 | Viewed by 10078

Abstract

Ongoing Sensor Web developments make a growing amount of heterogeneous sensor data available to smart devices. This is generating an increasing demand for homogeneous mechanisms to access, publish and share real-world information. This paper discusses, first, an architectural solution based on Next Generation [...] Read more.

Ongoing Sensor Web developments make a growing amount of heterogeneous sensor data available to smart devices. This is generating an increasing demand for homogeneous mechanisms to access, publish and share real-world information. This paper discusses, first, an architectural solution based on Next Generation Networks: a pilot Telco Ubiquitous Sensor Network (USN) Platform that embeds several OGC^® Sensor Web services. This platform has already been deployed in large scale projects. Second, the USN-Platform is extended to explore a first approach to Semantic Sensor Web principles and technologies, so that smart devices can access Sensor Web data, allowing them also to share richer (semantically interpreted) information. An experimental scenario is presented: a smart car that consumes and produces real-world information which is integrated into the Semantic Sensor Web through a Telco USN-Platform. Performance tests revealed that observation publishing times with our experimental system were well within limits compatible with the adequate operation of smart safety assistance systems in vehicles. On the other hand, response times for complex queries on large repositories may be inappropriate for rapid reaction needs. Full article

(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Spain 2013)

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3782 KiB

Open AccessArticle

Application of an Electronic Nose Instrument to Fast Classification of Polish Honey Types

by Tomasz Dymerski, Jacek Gębicki, Waldemar Wardencki and Jacek Namieśnik

Sensors 2014, 14(6), 10709-10724; https://doi.org/10.3390/s140610709 - 18 Jun 2014

Cited by 55 | Viewed by 7492

Abstract

The paper presents practical utilization of an electronic nose prototype, based on the FIGARO semiconductor sensors, in fast classification of Polish honey types—acacia flower, linden flower, rape, buckwheat and honeydew ones. A set of thermostating modules of the prototype provided gradient temperature characteristics [...] Read more.

The paper presents practical utilization of an electronic nose prototype, based on the FIGARO semiconductor sensors, in fast classification of Polish honey types—acacia flower, linden flower, rape, buckwheat and honeydew ones. A set of thermostating modules of the prototype provided gradient temperature characteristics of barbotage-prepared gas mixtures and stable measurement conditions. Three chemometric data analysis methods were employed for the honey samples classification: principal component analysis (PCA), linear discriminant analysis (LDA) and cluster analysis (CA) with the furthest neighbour method. The investigation confirmed usefulness of this type of instrument in correct classification of all aforementioned honey types. In order to provide optimum measurement conditions during honey samples classification the following parameters were selected: volumetric flow rate of carrier gas—15 L/h, barbotage temperature—35 °C, time of sensor signal acquisition since barbotage process onset—60 s. Chemometric analysis allowed discrimination of three honey types using PCA and CA and all five honey types with LDA. The reproducibility of 96% of the results was within the range 4.9%–8.6% CV. Full article

(This article belongs to the Section Chemical Sensors)

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597 KiB

Open AccessArticle

Detecting Falls with Wearable Sensors Using Machine Learning Techniques

by Ahmet Turan Özdemir and Billur Barshan

Sensors 2014, 14(6), 10691-10708; https://doi.org/10.3390/s140610691 - 18 Jun 2014

Cited by 308 | Viewed by 45502

Abstract

Falls are a serious public health problem and possibly life threatening for people in fall risk groups. We develop an automated fall detection system with wearable motion sensor units fitted to the subjects’ body at six different positions. Each unit comprises three tri-axial [...] Read more.

Falls are a serious public health problem and possibly life threatening for people in fall risk groups. We develop an automated fall detection system with wearable motion sensor units fitted to the subjects’ body at six different positions. Each unit comprises three tri-axial devices (accelerometer, gyroscope, and magnetometer/compass). Fourteen volunteers perform a standardized set of movements including 20 voluntary falls and 16 activities of daily living (ADLs), resulting in a large dataset with 2520 trials. To reduce the computational complexity of training and testing the classifiers, we focus on the raw data for each sensor in a 4 s time window around the point of peak total acceleration of the waist sensor, and then perform feature extraction and reduction. Most earlier studies on fall detection employ rule-based approaches that rely on simple thresholding of the sensor outputs. We successfully distinguish falls from ADLs using six machine learning techniques (classifiers): the k-nearest neighbor (k-NN) classifier, least squares method (LSM), support vector machines (SVM), Bayesian decision making (BDM), dynamic time warping (DTW), and artificial neural networks (ANNs). We compare the performance and the computational complexity of the classifiers and achieve the best results with the k-NN classifier and LSM, with sensitivity, specificity, and accuracy all above 99%. These classifiers also have acceptable computational requirements for training and testing. Our approach would be applicable in real-world scenarios where data records of indeterminate length, containing multiple activities in sequence, are recorded. Full article

(This article belongs to the Section Physical Sensors)

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Sensors, Volume 14, Issue 6 (June 2014) – 96 articles , Pages 9369-11277

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