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Sensors, Volume 19, Issue 20 (October-2 2019)

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Open AccessArticle
An Alignment Method for Strapdown Inertial Navigation Systems Assisted by Doppler Radar on a Vehicle-Borne Moving Base
Sensors 2019, 19(20), 4577; https://doi.org/10.3390/s19204577 (registering DOI) - 21 Oct 2019
Abstract
In this study, we investigated a novel method for high-accuracy autonomous alignment of a strapdown inertial navigation system assisted by Doppler radar on a vehicle-borne moving base, which effectively avoids the measurement errors caused by wheel-slip or vehicle-sliding. Using the gyroscopes in a [...] Read more.
In this study, we investigated a novel method for high-accuracy autonomous alignment of a strapdown inertial navigation system assisted by Doppler radar on a vehicle-borne moving base, which effectively avoids the measurement errors caused by wheel-slip or vehicle-sliding. Using the gyroscopes in a strapdown inertial navigation system and Doppler radar, we calculated the dead reckoning, analyzed the error sources of the dead reckoning system, and established an error model. Then the errors of the strapdown inertial navigation system and dead reckoning system were treated as the states. Besides velocity information, attitude information was cleverly introduced into the alignment measurement to improve alignment accuracy and reduce alignment time. Therefore, the first measurement was the difference between the output attitude and velocity of the strapdown inertial navigation system and the corresponding signals from the dead reckoning system. In order to further improve the alignment accuracy, more measurement information was introduced by using the vehicle motion constraint, that is, the velocity output projection of strapdown inertial navigation system along the transverse and vertical direction of the vehicle body was also used as the second measurement. Then the corresponding state and measurement equations were established, and the Kalman filter algorithm was used for assisted alignment filtering. The simulation results showed that, with a moving base, the misalignment angle estimation accuracy was better than 0.5’ in the east direction, 0.4’ in the north direction, and 3.2’ in the vertical direction. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
A SINS/DVL Integrated Positioning System through Filtering Gain Compensation Adaptive Filtering
Sensors 2019, 19(20), 4576; https://doi.org/10.3390/s19204576 (registering DOI) - 21 Oct 2019
Abstract
Because of the complex task environment, long working distance, and random drift of the gyro, the positioning error gradually diverges with time in the design of a strapdown inertial navigation system (SINS)/Doppler velocity log (DVL) integrated positioning system. The use of velocity information [...] Read more.
Because of the complex task environment, long working distance, and random drift of the gyro, the positioning error gradually diverges with time in the design of a strapdown inertial navigation system (SINS)/Doppler velocity log (DVL) integrated positioning system. The use of velocity information in the DVL system cannot completely suppress the divergence of the SINS navigation error, which will result in low positioning accuracy and instability. To address this problem, this paper proposes a SINS/DVL integrated positioning system based on a filtering gain compensation adaptive filtering technology that considers the source of error in SINS and the mechanism that influences the positioning results. In the integrated positioning system, an organic combination of a filtering gain compensation adaptive filter and a filtering gain compensation strong tracking filter is explored to fuse position information to obtain higher accuracy and a more stable positioning result. Firstly, the system selects the indirect filtering method and uses the integrated positioning error to model the navigation parameters of the system. Then, a filtering gain compensation adaptive filtering method is developed by using the filtering gain compensation algorithm based on the error statistics of the positioning parameters. The positioning parameters of the system are filtered and information on errors in the navigation parameters is obtained. Finally, integrated with the positioning parameter error information, the positioning parameters of the system are solved, and high-precision positioning results are obtained to accurately position autonomous underwater vehicles (AUVs). The simulation results show that the SINS/DVL integrated positioning method, based on the filtering gain compensation adaptive filtering technology, can effectively enhance the positioning accuracy. Full article
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Open AccessArticle
Sensors for Expert Grip Force Profiling: Towards Benchmarking Manual Control of a Robotic Device for Surgical Tool Movements
Sensors 2019, 19(20), 4575; https://doi.org/10.3390/s19204575 (registering DOI) - 21 Oct 2019
Abstract
STRAS (Single access Transluminal Robotic Assistant for Surgeons) is a new robotic system based on the Anubis® platform of Karl Storz for application to intra-luminal surgical procedures. Pre-clinical testing of STRAS has recently permitted to demonstrate [...] Read more.
STRAS (Single access Transluminal Robotic Assistant for Surgeons) is a new robotic system based on the Anubis® platform of Karl Storz for application to intra-luminal surgical procedures. Pre-clinical testing of STRAS has recently permitted to demonstrate major advantages of the system in comparison with classic procedures. Benchmark methods permitting to establish objective criteria for ‘expertise’ need to be worked out now to effectively train surgeons on this new system in the near future. STRAS consists of three cable-driven sub-systems, one endoscope serving as guide, and two flexible instruments. The flexible instruments have three degrees of freedom and can be teleoperated by a single user via two specially designed master interfaces. In this study, small force sensors sewn into a wearable glove to ergonomically fit the master handles of the robotic system were employed for monitoring the forces applied by an expert and a trainee (complete novice) during all the steps of surgical task execution in a simulator task (4-step-pick-and-drop). Analysis of grip-force profiles is performed sensor by sensor to bring to the fore specific differences in handgrip force profiles in specific sensor locations on anatomically relevant parts of the fingers and hand controlling the master/slave system. Full article
(This article belongs to the Special Issue Wearable and Nearable Biosensors and Systems for Healthcare)
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Open AccessArticle
Dropping Counter: A Detection Algorithm for Identifying Odour-Evoked Responses from Noisy Electroantennograms Measured by a Flying Robot
Sensors 2019, 19(20), 4574; https://doi.org/10.3390/s19204574 (registering DOI) - 21 Oct 2019
Abstract
The electroantennogram (EAG) is a technique used for measuring electrical signals from the antenna of an insect. Its rapid response time, quick recovery speed, and high sensitivity make it suitable for odour-tracking tasks employing mobile robots. However, its application to flying robots has [...] Read more.
The electroantennogram (EAG) is a technique used for measuring electrical signals from the antenna of an insect. Its rapid response time, quick recovery speed, and high sensitivity make it suitable for odour-tracking tasks employing mobile robots. However, its application to flying robots has not been extensively studied owing to the electrical and mechanical noises generated. In this study, we investigated the characteristics of the EAG mounted on a tethered flying quadcopter and developed a special counter-based algorithm for detecting the odour-generated responses. As the EAG response is negative, the algorithm creates a window and compares the values inside it. Once a value is smaller than the first one, the counter will increase by one and finally turns the whole signal into a clearer odour stimulated result. By experimental evaluation, the new algorithm gives a higher cross-correlation coefficient when compared with the fixed-threshold method. The result shows that the accuracy of this novel algorithm for recognising odour-evoked EAG signals from noise exceeds that of the traditional method; furthermore, the use of insect antennae as odour sensors for flying robots is demonstrated to be feasible. Full article
(This article belongs to the Section Chemical Sensors)
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Open AccessArticle
3D Reconstruction of Slug Flow in Mini-Channels with a Simple and Low-Cost Optical Sensor
Sensors 2019, 19(20), 4573; https://doi.org/10.3390/s19204573 (registering DOI) - 21 Oct 2019
Abstract
The present work provides a new approach for 3D image reconstruction of gas-liquid two-phase flow (GLF) in mini-channels based on a new optical sensor. The sensor consists of a vertical and a horizontal photodiode array. Firstly, with the optical signals obtained by the [...] Read more.
The present work provides a new approach for 3D image reconstruction of gas-liquid two-phase flow (GLF) in mini-channels based on a new optical sensor. The sensor consists of a vertical and a horizontal photodiode array. Firstly, with the optical signals obtained by the vertical array, a measurement model developed by Support Vector Regression (SVR) was used to determine the cross-sectional information. The determined information was further used to reconstruct cross-sectional 2D images. Then, the gas velocity was calculated according to the signals obtained by the horizontal array, and the spatial interval of the 2D images was determined. Finally, 3D images were reconstructed by piling up the 2D images. In this work, the cross-sectional gas-liquid interface was considered as circular, and high-speed visualization was utilized to provide the reference values. The image deformation caused by channel wall was also considered. Experiments of slug flow in a channel with an inner diameter of 4.0 mm were carried out. The results verify the feasibility of the proposed 3D reconstruction method. The proposed method has the advantages of simple construct, low cost, and easily multipliable. The reconstructed 3D images can provide detailed and undistorted information of flow structure, which could further improve the measurement accuracy of other important parameters of gas-liquid two-phase flow, such as void fraction, pressure drop, and flow pattern. Full article
(This article belongs to the Section Optical Sensors)
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Open AccessArticle
Two-Wired Active Spring-Loaded Dry Electrodes for EEG Measurements
Sensors 2019, 19(20), 4572; https://doi.org/10.3390/s19204572 (registering DOI) - 21 Oct 2019
Abstract
Dry contact electrode-based EEG acquisition is one of the easiest ways to obtain neural information from the human brain, providing many advantages such as rapid installation, and enhanced wearability. However, high contact impedance due to insufficient electrical coupling at the electrode-scalp interface still [...] Read more.
Dry contact electrode-based EEG acquisition is one of the easiest ways to obtain neural information from the human brain, providing many advantages such as rapid installation, and enhanced wearability. However, high contact impedance due to insufficient electrical coupling at the electrode-scalp interface still remains a critical issue. In this paper, a two-wired active dry electrode system is proposed by combining finger-shaped spring-loaded probes and active buffer circuits. The shrinkable probes and bootstrap topology-based buffer circuitry provide reliable electrical coupling with an uneven and hairy scalp and effective input impedance conversion along with low input capacitance. Through analysis of the equivalent circuit model, the proposed electrode was carefully designed by employing off-the-shelf discrete components and a low-noise zero-drift amplifier. Several electrical evaluations such as noise spectral density measurements and input capacitance estimation were performed together with simple experiments for alpha rhythm detection. The experimental results showed that the proposed electrode is capable of clear detection for the alpha rhythm activation, with excellent electrical characteristics such as low-noise of 1.131 μVRMS and 32.3% reduction of input capacitance. Full article
(This article belongs to the Special Issue Sensors for Affective Computing and Sentiment Analysis)
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Open AccessArticle
Life-Cycle Modeling of Structural Defects via Computational Geometry and Time-Series Forecasting
Sensors 2019, 19(20), 4571; https://doi.org/10.3390/s19204571 (registering DOI) - 21 Oct 2019
Abstract
The evaluation of geometric defects is necessary in order to maintain the integrity of structures over time. These assessments are designed to detect damages of structures and ideally help inspectors to estimate the remaining life of structures. Current methodologies for monitoring structural systems, [...] Read more.
The evaluation of geometric defects is necessary in order to maintain the integrity of structures over time. These assessments are designed to detect damages of structures and ideally help inspectors to estimate the remaining life of structures. Current methodologies for monitoring structural systems, while providing useful information about the current state of a structure, are limited in the monitoring of defects over time and in linking them to predictive simulation. This paper presents a new approach to the predictive modeling of geometric defects. A combination of segments from point clouds are parametrized using the convex hull algorithm to extract features from detected defects, and a stochastic dynamic model is then adapted to these features to model the evolution of the hull over time. Describing a defect in terms of its parameterized hull enables consistent temporal tracking for predictive purposes, while implicitly reducing data dimensionality and complexity as well. In this study, two-dimensional (2D) point clouds analogous to information derived from point clouds were firstly generated over simulated life cycles. The evolutions of point cloud hull parameterizations were modeled as stochastic dynamical processes via autoregressive integrated moving average (ARIMA) and vectorized autoregression (VAR) and compared against ground truth. The results indicate that this convex hull approach provides consistent and accurate representations of defect evolution across a range of defect topologies and is reasonably robust to noisy measurements; however, assumptions regarding the underlying dynamical process play a significant the role in predictive accuracy. The results were then validated on experimental data from fatigue testing with high accuracy. Longer term, the results of this work will support finite element model updating for predictive analysis of structural capacity. Full article
(This article belongs to the Section State-of-the-Art Sensors Technologies)
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Open AccessArticle
Coherent Pulse-Compression Lidar Based on 90-Degree Optical Hybrid
Sensors 2019, 19(20), 4570; https://doi.org/10.3390/s19204570 (registering DOI) - 21 Oct 2019
Abstract
A coherent pulse-compression lidar system based on a 90-degree optical hybrid is demonstrated in this paper. In amplitude modulation (AM) mode, the returned RF chirp signal will be influenced by a random phase difference between local oscillator and echo light, causing fluctuations in [...] Read more.
A coherent pulse-compression lidar system based on a 90-degree optical hybrid is demonstrated in this paper. In amplitude modulation (AM) mode, the returned RF chirp signal will be influenced by a random phase difference between local oscillator and echo light, causing fluctuations in the ranging results, and as a result the detection probability is small. By using the 90-degree optical hybrid, two orthogonal complementary signals are obtained to stabilize the result so as to increase the detection probability. We performed an experiment to measure the distance of a white printed wall which is about 65 m away from the system. The detection probability increased from 65% to 99.88%, and the precision is improved from 0.42 m to 0.27 m. Full article
(This article belongs to the Section Optical Sensors)
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Open AccessEditorial
Special Issue on “Terrestrial Laser Scanning”: Editors’ Notes
Sensors 2019, 19(20), 4569; https://doi.org/10.3390/s19204569 (registering DOI) - 21 Oct 2019
Abstract
In this editorial, we provide an overview of the content of the special issue on “Terrestrial Laser Scanning”. The aim of this Special Issue is to bring together innovative developments and applications of terrestrial laser scanning (TLS), understood in a broad sense. Thus, [...] Read more.
In this editorial, we provide an overview of the content of the special issue on “Terrestrial Laser Scanning”. The aim of this Special Issue is to bring together innovative developments and applications of terrestrial laser scanning (TLS), understood in a broad sense. Thus, although most contributions mainly involve the use of laser-based systems, other alternative technologies that also allow for obtaining 3D point clouds for the measurement and the 3D characterization of terrestrial targets, such as photogrammetry, are also considered. The 15 published contributions are mainly focused on the applications of TLS to the following three topics: TLS performance and point cloud processing, applications to civil engineering, and applications to plant characterization. Full article
(This article belongs to the Special Issue Terrestrial Laser Scanning)
Open AccessArticle
Improved Multistage In-Motion Attitude Determination Alignment Method for Strapdown Inertial Navigation System
Sensors 2019, 19(20), 4568; https://doi.org/10.3390/s19204568 - 21 Oct 2019
Abstract
This paper derives an improved multistage in-motion attitude determination alignment (IMADA) for strapdown inertial navigation system, which integrates the traditional IMADA and the designed dual velocity-modeling IMADA, as well as the multiple repeated alignment process, to address the principled model errors and the [...] Read more.
This paper derives an improved multistage in-motion attitude determination alignment (IMADA) for strapdown inertial navigation system, which integrates the traditional IMADA and the designed dual velocity-modeling IMADA, as well as the multiple repeated alignment process, to address the principled model errors and the calculation errors of traditional V b -aided IMADA. With the proposed algorithm, not only the designed drawbacks of traditional V b -based IMADA can be solved, but also the degradation phenomenon of high-level alignment for multistage IMADA would be largely less. Moreover, the degradation of the alignment accuracy with the vehicle velocity is also removed. Finally, the 30 groups of car-mounted experiments and the Monte Carlo simulation experiments with the navigation-grade SINS are carried out to demonstrate the validity of the proposed algorithm. The results show that the number of the heading degradation of the second-level alignment is reduced to 10 as compared the traditional number 20. Moreover, the alignment accuracy of heading is improved by 23%. Even with the different speeds of 20 m/s, 60 m/s, 80 m/s, the heading alignment accuracies are 1.3063°, 1.3102°, 1.3564° and are still almost the same. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
Implementation of Sensing and Actuation Capabilities for IoT Devices Using oneM2M Platforms
Sensors 2019, 19(20), 4567; https://doi.org/10.3390/s19204567 - 21 Oct 2019
Abstract
In this paper, we present an implementation work of sensing and actuation capabilities for IoT devices using the oneM2M standard-based platforms. We mainly focus on the heterogeneity of the hardware interfaces employed in IoT devices. For IoT devices (i.e., Internet-connected embedded systems) to [...] Read more.
In this paper, we present an implementation work of sensing and actuation capabilities for IoT devices using the oneM2M standard-based platforms. We mainly focus on the heterogeneity of the hardware interfaces employed in IoT devices. For IoT devices (i.e., Internet-connected embedded systems) to perform sensing and actuation capabilities in a standardized manner, a well-designed middleware solution will be a crucial part of IoT platform. Accordingly, we propose an oneM2M standard-based IoT platform (called nCube) incorporated with a set of tiny middleware programs (called TAS) responsible for translating sensing values and actuation commands into oneM2M-defined resources accessible in Web-based applications. All the source codes for the oneM2M middleware platform and smartphone application are available for free in the GitHub repositories. The full details on the implementation work and open-source contributions are described. Full article
(This article belongs to the Special Issue Internet of Things Middleware Platforms and Sensing Infrastructure)
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Open AccessArticle
Modeling of the Return Current in a Light-Addressable Potentiometric Sensor
Sensors 2019, 19(20), 4566; https://doi.org/10.3390/s19204566 - 21 Oct 2019
Abstract
A light-addressable potentiometric sensor (LAPS) is a chemical sensor with a field-effect structure based on semiconductor. Its response to the analyte concentration is read out in the form of a photocurrent generated by illuminating the semiconductor with a modulated light beam. As stated [...] Read more.
A light-addressable potentiometric sensor (LAPS) is a chemical sensor with a field-effect structure based on semiconductor. Its response to the analyte concentration is read out in the form of a photocurrent generated by illuminating the semiconductor with a modulated light beam. As stated in its name, a LAPS is capable of spatially resolved measurement using a scanning light beam. Recently, it has been pointed out that a part of the signal current is lost by the return current due to capacitive coupling between the solution and the semiconductor, which may seriously affect the sensor performance such as the signal-to-noise ratio, the spatial resolution, and the sensitivity. In this study, a circuit model for the return current is proposed to study its dependence on various parameters such as the diameter of contact area, the modulation frequency, the specific conductivity of the solution, and the series resistance of the circuit. It is suggested that minimization of the series resistance of the circuit is of utmost importance in order to avoid the influence of the return current. The results of calculation based on this model are compared with experimental results, and its applicability and limitation are discussed. Full article
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Open AccessArticle
eHomeSeniors Dataset: An Infrared Thermal Sensor Dataset for Automatic Fall Detection Research
Sensors 2019, 19(20), 4565; https://doi.org/10.3390/s19204565 (registering DOI) - 21 Oct 2019
Abstract
Automatic fall detection is a very active research area, which has grown explosively since the 2010s, especially focused on elderly care. Rapid detection of falls favors early awareness from the injured person, reducing a series of negative consequences in the health of the [...] Read more.
Automatic fall detection is a very active research area, which has grown explosively since the 2010s, especially focused on elderly care. Rapid detection of falls favors early awareness from the injured person, reducing a series of negative consequences in the health of the elderly. Currently, there are several fall detection systems (FDSs), mostly based on predictive and machine-learning approaches. These algorithms are based on different data sources, such as wearable devices, ambient-based sensors, or vision/camera-based approaches. While wearable devices like inertial measurement units (IMUs) and smartphones entail a dependence on their use, most image-based devices like Kinect sensors generate video recordings, which may affect the privacy of the user. Regardless of the device used, most of these FDSs have been tested only in controlled laboratory environments, and there are still no mass commercial FDS. The latter is partly due to the impossibility of counting, for ethical reasons, with datasets generated by falls of real older adults. All public datasets generated in laboratory are performed by young people, without considering the differences in acceleration and falling features of older adults. Given the above, this article presents the eHomeSeniors dataset, a new public dataset which is innovative in at least three aspects: first, it collects data from two different privacy-friendly infrared thermal sensors; second, it is constructed by two types of volunteers: normal young people (as usual) and performing artists, with the latter group assisted by a physiotherapist to emulate the real fall conditions of older adults; and third, the types of falls selected are the result of a thorough literature review. Full article
(This article belongs to the Special Issue Sensor Technology for Smart Homes)
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Open AccessArticle
Application of a Fluorescent Probe for the Online Measurement of PM-Bound Reactive Oxygen Species in Chamber and Ambient Studies
Sensors 2019, 19(20), 4564; https://doi.org/10.3390/s19204564 - 21 Oct 2019
Abstract
This manuscript details the application of a profluorescent nitroxide (PFN) for the online quantification of radical concentrations on particulate matter (PM) using an improved Particle Into Nitroxide Quencher (PINQ). A miniature flow-through fluorimeter developed specifically for use with the 9,10-bis(phenylethynyl)anthracene-nitroxide (BPEAnit) probe was [...] Read more.
This manuscript details the application of a profluorescent nitroxide (PFN) for the online quantification of radical concentrations on particulate matter (PM) using an improved Particle Into Nitroxide Quencher (PINQ). A miniature flow-through fluorimeter developed specifically for use with the 9,10-bis(phenylethynyl)anthracene-nitroxide (BPEAnit) probe was integrated into the PINQ, along with automated gas phase corrections through periodic high efficiency particle arrestor (HEPA) filtering. The resulting instrument is capable of unattended sampling and was operated with a minimum time resolution of 2.5 min. Details of the fluorimeter design and examples of data processing are provided, and results from a chamber study of side-stream cigarette smoke and ambient monitoring campaign in Guangzhou, China are presented. Primary cigarette smoke was shown to have both short-lived (t1/2 = 27 min) and long-lived (t1/2 = indefinite) PM-bound reactive oxygen species (ROS) components which had previously only been observed in secondary organic aerosol (SOA). Full article
(This article belongs to the Special Issue Fluorescence-Based Sensors)
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Open AccessArticle
Gas Sensing Properties of Perovskite Decorated Graphene at Room Temperature
Sensors 2019, 19(20), 4563; https://doi.org/10.3390/s19204563 - 20 Oct 2019
Viewed by 177
Abstract
This paper explores the gas sensing properties of graphene nanolayers decorated with lead halide perovskite (CH3NH3PbBr3) nanocrystals to detect toxic gases such as ammonia (NH3) and nitrogen dioxide (NO2). A chemical-sensitive semiconductor film [...] Read more.
This paper explores the gas sensing properties of graphene nanolayers decorated with lead halide perovskite (CH3NH3PbBr3) nanocrystals to detect toxic gases such as ammonia (NH3) and nitrogen dioxide (NO2). A chemical-sensitive semiconductor film based on graphene has been achieved, being decorated with CH3NH3PbBr3 perovskite (MAPbBr3) nanocrystals (NCs) synthesized, and characterized by several techniques, such as field emission scanning electron microscopy, transmission electron microscopy and X-ray photoelectron spectroscopy. Reversible responses were obtained towards NO2 and NH3 at room temperature, demonstrating an enhanced sensitivity when the graphene is decorated by MAPbBr3 NCs. Furthermore, the effect of ambient moisture was extensively studied, showing that the use of perovskite NCs in gas sensors can become a promising alternative to other gas sensitive materials, due to the protective character of graphene, resulting from its high hydrophobicity. Besides, a gas sensing mechanism is proposed to understand the effects of MAPbBr3 sensing properties. Full article
(This article belongs to the Special Issue Multisensor Arrays for Environmental Monitoring)
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Open AccessArticle
A New Method for Total Fat Detection in Raw Milk Based on Dual Low-Coherence Interferometer
Sensors 2019, 19(20), 4562; https://doi.org/10.3390/s19204562 - 20 Oct 2019
Viewed by 147
Abstract
The present work experimentally demonstrates a multimode fiber optic sensing setup for total fat detection in raw milk samples. The optical fiber arrangement incorporates a low-coherence Fabry–Perot cavity operating in dual response. The system provides a phase modulation for a total fat range [...] Read more.
The present work experimentally demonstrates a multimode fiber optic sensing setup for total fat detection in raw milk samples. The optical fiber arrangement incorporates a low-coherence Fabry–Perot cavity operating in dual response. The system provides a phase modulation for a total fat range from 0.97% to 4.36%. Here, the protein remains constant at 3%. The data indicate that maximum sensitivity close to 616 pm/%fat could be achieved at optimal wavelength operation (500 nm). In addition, the system presented a minimal repeatability error measurement of 0.08%, cross-sensitivity between protein and fat of 0.134, and a regression coefficient of r2=0.9763. A thermal analysis was also performed, which indicate the temperature immunity of the system. The proposed method represents a low-cost alternative to detect minimal fat variations in raw cow milk. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle
An Exploration of Machine Learning Methods for Robust Boredom Classification Using EEG and GSR Data
Sensors 2019, 19(20), 4561; https://doi.org/10.3390/s19204561 - 20 Oct 2019
Viewed by 162
Abstract
In recent years, affective computing has been actively researched to provide a higher level of emotion-awareness. Numerous studies have been conducted to detect the user’s emotions from physiological data. Among a myriad of target emotions, boredom, in particular, has been suggested to cause [...] Read more.
In recent years, affective computing has been actively researched to provide a higher level of emotion-awareness. Numerous studies have been conducted to detect the user’s emotions from physiological data. Among a myriad of target emotions, boredom, in particular, has been suggested to cause not only medical issues but also challenges in various facets of daily life. However, to the best of our knowledge, no previous studies have used electroencephalography (EEG) and galvanic skin response (GSR) together for boredom classification, although these data have potential features for emotion classification. To investigate the combined effect of these features on boredom classification, we collected EEG and GSR data from 28 participants using off-the-shelf sensors. During data acquisition, we used a set of stimuli comprising a video clip designed to elicit boredom and two other video clips of entertaining content. The collected samples were labeled based on the participants’ questionnaire-based testimonies on experienced boredom levels. Using the collected data, we initially trained 30 models with 19 machine learning algorithms and selected the top three candidate classifiers. After tuning the hyperparameters, we validated the final models through 1000 iterations of 10-fold cross validation to increase the robustness of the test results. Our results indicated that a Multilayer Perceptron model performed the best with a mean accuracy of 79.98% (AUC: 0.781). It also revealed the correlation between boredom and the combined features of EEG and GSR. These results can be useful for building accurate affective computing systems and understanding the physiological properties of boredom. Full article
Open AccessArticle
Parylene-Coated Polytetrafluoroethylene-Membrane-Based Portable Urea Sensor for Real-Time Monitoring of Urea in Peritoneal Dialysate
Sensors 2019, 19(20), 4560; https://doi.org/10.3390/s19204560 - 20 Oct 2019
Viewed by 150
Abstract
A portable urea sensor for use in fast flow conditions was fabricated using porous polytetrafluoroethylene (PTFE) membranes coated with amine-functionalized parylene, parylene-A, by vapor deposition. The urea-hydrolyzing enzyme urease was immobilized on the parylene-A-coated PTFE membranes using glutaraldehyde. The urease-immobilized membranes were assembled [...] Read more.
A portable urea sensor for use in fast flow conditions was fabricated using porous polytetrafluoroethylene (PTFE) membranes coated with amine-functionalized parylene, parylene-A, by vapor deposition. The urea-hydrolyzing enzyme urease was immobilized on the parylene-A-coated PTFE membranes using glutaraldehyde. The urease-immobilized membranes were assembled in a polydimethylsiloxane (PDMS) fluidic chamber, and a screen-printed carbon three-electrode system was used for electrochemical measurements. The success of urease immobilization was confirmed using scanning electron microscopy, and fourier-transform infrared spectroscopy. The optimum concentration of urease for immobilization on the parylene-A-coated PTFE membranes was determined to be 48 mg/mL, and the optimum number of membranes in the PDMS chamber was found to be eight. Using these optimized conditions, we fabricated the urea biosensor and monitored urea samples under various flow rates ranging from 0.5 to 10 mL/min in the flow condition using chronoamperometry. To test the applicability of the sensor for physiological samples, we used it for monitoring urea concentration in the waste peritoneal dialysate of a patient with chronic renal failure, at a flow rate of 0.5 mL/min. This developed urea biosensor is considered applicable for (portable) applications, such as artificial kidney systems and portable dialysis systems. Full article
(This article belongs to the Section Biosensors)
Open AccessArticle
A Cloud-based Middleware for Self-Adaptive IoT-Collaboration Services
Sensors 2019, 19(20), 4559; https://doi.org/10.3390/s19204559 - 20 Oct 2019
Viewed by 163
Abstract
The middleware framework for IoT collaboration services should provide efficient solutions to context awareness and uncertainty issues among multiple collaboration domains. However, existing middleware frameworks are mostly limited to a single system, and developing self-adaptive IoT collaboration services using existing frameworks requires developers [...] Read more.
The middleware framework for IoT collaboration services should provide efficient solutions to context awareness and uncertainty issues among multiple collaboration domains. However, existing middleware frameworks are mostly limited to a single system, and developing self-adaptive IoT collaboration services using existing frameworks requires developers to take considerable time and effort. Furthermore, the developed IoT collaboration services are often dependent on a particular domain, which cannot easily be referenced in other domains. This paper proposes a cloud-based middleware framework that provides a set of cloud services for self-adaptive IoT collaboration services. The proposed middleware framework is generic in the sense that it clearly separates domain-dependent components from the layers that leverage existing middleware frameworks. In addition, the proposed framework allows developers to upload domain-dependent components onto the cloud, search for registered components, and launch Virtual Machine (VM) running a new MAPE cycle via a convenient web-based interface. The feasibility of the proposed framework has been shown with a simulation of an IoT collaboration service that traces a criminal suspect. The performance evaluation shows that the proposed middleware framework runs with an overhead of only 6% compared to pure Java-based middleware and is scalable as the number of VMs increases up to 16. Full article
(This article belongs to the Special Issue Internet of Things Middleware Platforms and Sensing Infrastructure)
Open AccessArticle
A New Calibration Circuit Design to Reduce Drift Effect of RuO2 Urea Biosensors
Sensors 2019, 19(20), 4558; https://doi.org/10.3390/s19204558 - 20 Oct 2019
Viewed by 157
Abstract
The goal of this study was to reduce the drift effect of RuO2 urea biosensors. A new calibration circuit (NCC) based on the voltage regulation technique with the advantage of having a simple structure was presented. To keep its simplicity, the proposed [...] Read more.
The goal of this study was to reduce the drift effect of RuO2 urea biosensors. A new calibration circuit (NCC) based on the voltage regulation technique with the advantage of having a simple structure was presented. To keep its simplicity, the proposed NCC was composed of a non-inverting amplifier and a voltage calibrating circuit. A ruthenium oxide (RuO2) urea biosensor was fabricated to test the calibrating characteristics of the drift rate of the proposed NCC. The experiment performed in this study was divided into two main stages. For the first stage, a sound RuO2 urea biosensor testing environment was set-up. The RuO2 urea sensing film was immersed in the urea solution for 12 h and the response voltage was measured using the voltage-time (V–T) measurement system and the proposed NCC. The results of the first stage showed that the RuO2 urea biosensor has an average sensitivity of 1.860 mV/(mg/dL) and has a linearity of 0.999 which means that the RuO2 urea biosensor had been well fabricated. The second stage of the experiment verified the proposed NCC’s functions, and the results indicated that the proposed NCC reduced the drift rate of RuO2 urea biosensor to 0.02 mV/hr (98.77% reduction). Full article
(This article belongs to the Special Issue Potentiometric Bio/Chemical Sensing)
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Open AccessReview
A Review of Force Myography Research and Development
Sensors 2019, 19(20), 4557; https://doi.org/10.3390/s19204557 - 20 Oct 2019
Viewed by 143
Abstract
Information about limb movements can be used for monitoring physical activities or for human-machine-interface applications. In recent years, a technique called Force Myography (FMG) has gained ever-increasing traction among researchers to extract such information. FMG uses force sensors to register the variation of [...] Read more.
Information about limb movements can be used for monitoring physical activities or for human-machine-interface applications. In recent years, a technique called Force Myography (FMG) has gained ever-increasing traction among researchers to extract such information. FMG uses force sensors to register the variation of muscle stiffness patterns around a limb during different movements. Using machine learning algorithms, researchers are able to predict many different limb activities. This review paper presents state-of-art research and development on FMG technology in the past 20 years. It summarizes the research progress in both the hardware design and the signal processing techniques. It also discusses the challenges that need to be solved before FMG can be used in an everyday scenario. This paper aims to provide new insight into FMG technology and contribute to its advancement. Full article
(This article belongs to the Special Issue Sensors for Posture and Human Motion Recognition)
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Open AccessArticle
Infrared and Visible Image Fusion through Details Preservation
Sensors 2019, 19(20), 4556; https://doi.org/10.3390/s19204556 - 20 Oct 2019
Viewed by 149
Abstract
In many actual applications, fused image is essential to contain high-quality details for achieving a comprehensive representation of the real scene. However, existing image fusion methods suffer from loss of details because of the error accumulations of sequential tasks. This paper proposes a [...] Read more.
In many actual applications, fused image is essential to contain high-quality details for achieving a comprehensive representation of the real scene. However, existing image fusion methods suffer from loss of details because of the error accumulations of sequential tasks. This paper proposes a novel fusion method to preserve details of infrared and visible images by combining new decomposition, feature extraction, and fusion scheme. For decomposition, different from the most decomposition methods by guided filter, the guidance image contains only the strong edge of the source image but no other interference information so that rich tiny details can be decomposed into the detailed part. Then, according to the different characteristics of infrared and visible detail parts, a rough convolutional neural network (CNN) and a sophisticated CNN are designed so that various features can be fully extracted. To integrate the extracted features, we also present a multi-layer features fusion strategy through discrete cosine transform (DCT), which not only highlights significant features but also enhances details. Moreover, the base parts are fused by weighting method. Finally, the fused image is obtained by adding the fused detail and base part. Different from the general image fusion methods, our method not only retains the target region of source image but also enhances background in the fused image. In addition, compared with state-of-the-art fusion methods, our proposed fusion method has many advantages, including (i) better visual quality of fused-image subjective evaluation, and (ii) better objective assessment for those images. Full article
(This article belongs to the Section Intelligent Sensors)
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Open AccessArticle
Optimal Target Assignment with Seamless Handovers for Networked Radars
Sensors 2019, 19(20), 4555; https://doi.org/10.3390/s19204555 - 19 Oct 2019
Viewed by 225
Abstract
This paper proposes a binary linear programming formulation for multiple target assignment of a radar network and demonstrates its applicability to obtain optimal solutions using an off-the-shelf mixed-integer linear programming solver. The goal of radar resource scheduling in this paper is to assign [...] Read more.
This paper proposes a binary linear programming formulation for multiple target assignment of a radar network and demonstrates its applicability to obtain optimal solutions using an off-the-shelf mixed-integer linear programming solver. The goal of radar resource scheduling in this paper is to assign the maximum number of targets by handing over targets between networked radar systems to overcome physical limitations such as the detection range and simultaneous tracking capability of each radar. To achieve this, time windows are generated considering the relation between each radar and target considering incoming target information. Numerical experiments using a local-scale simulation were performed to verify the functionality of the formulation and a sensitivity analysis was conducted to identify the trend of the results with respect to several parameters. Additional experiments performed for a large-scale (battlefield) scenario confirmed that the proposed formulation is valid and applicable for hundreds of targets and corresponding radar network systems composed of five distributed radars. The performance of the scheduling solutions using the proposed formulation was better than that of the general greedy algorithm as a heuristic approach in terms of objective value as well as the number of handovers. Full article
Open AccessArticle
Smartphone-Based 3D Indoor Pedestrian Positioning through Multi-Modal Data Fusion
Sensors 2019, 19(20), 4554; https://doi.org/10.3390/s19204554 - 19 Oct 2019
Viewed by 206
Abstract
Combining research areas of biomechanics and pedestrian dead reckoning (PDR) provides a very promising way for pedestrian positioning in environments where Global Positioning System (GPS) signals are degraded or unavailable. In recent years, the PDR systems based on a smartphone’s built-in inertial sensors [...] Read more.
Combining research areas of biomechanics and pedestrian dead reckoning (PDR) provides a very promising way for pedestrian positioning in environments where Global Positioning System (GPS) signals are degraded or unavailable. In recent years, the PDR systems based on a smartphone’s built-in inertial sensors have attracted much attention in such environments. However, smartphone-based PDR systems are facing various challenges, especially the heading drift, which leads to the phenomenon of estimated walking path passing through walls. In this paper, the 2D PDR system is implemented by using a pocket-worn smartphone, and then enhanced by introducing a map-matching algorithm that employs a particle filter to prevent the wall-crossing problem. In addition, to extend the PDR system for 3D applications, the smartphone’s built-in barometer is used to measure the pressure variation associated to the pedestrian’s vertical displacement. Experimental results show that the map-matching algorithm based on a particle filter can effectively solve the wall-crossing problem and improve the accuracy of indoor PDR. By fusing the barometer readings, the vertical displacement can be calculated to derive the floor transition information. Despite the inherent sensor noises and complex pedestrian movements, smartphone-based 3D pedestrian positioning systems have considerable potential for indoor location-based services (LBS). Full article
(This article belongs to the Special Issue Sensors for Biomechanics Application)
Open AccessArticle
Practical and Durable Flexible Strain Sensors Based on Conductive Carbon Black and Silicone Blends for Large Scale Motion Monitoring Applications
Sensors 2019, 19(20), 4553; https://doi.org/10.3390/s19204553 - 19 Oct 2019
Viewed by 179
Abstract
Presented is a flexible capacitive strain sensor, based on the low cost materials silicone (PDMS) and carbon black (CB), that was fabricated by casting and curing of successive silicone layers—a central PDMS dielectric layer bounded by PDMS/CB blend electrodes and packaged by exterior [...] Read more.
Presented is a flexible capacitive strain sensor, based on the low cost materials silicone (PDMS) and carbon black (CB), that was fabricated by casting and curing of successive silicone layers—a central PDMS dielectric layer bounded by PDMS/CB blend electrodes and packaged by exterior PDMS films. It was effectively characterized for large flexion-angle motion wearable applications, with strain sensing properties assessed over large strains (50%) and variations in temperature and humidity. Additionally, suitability for monitoring large tissue deformation was established by integration with an in vitro digestive model. The capacitive gauge factor was approximately constant at 0.86 over these conditions for the linear strain range (3 to 47%). Durability was established from consistent relative capacitance changes over 10,000 strain cycles, with varying strain frequency and elongation up to 50%. Wearability and high flexion angle human motion detection were demonstrated by integration with an elbow band, with clear detection of motion ranges up 90°. The device’s simple structure and fabrication method, low-cost materials and robust performance, offer promise for expanding the availability of wearable sensor systems. Full article
(This article belongs to the Special Issue Multi-Modal Sensors for Human Behavior Monitoring)
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Open AccessArticle
Underwater Acoustic Sensor Networks Node Localization Based on Compressive Sensing in Water Hydrology
Sensors 2019, 19(20), 4552; https://doi.org/10.3390/s19204552 - 19 Oct 2019
Viewed by 190
Abstract
Groundwater is an important source of human activities, agriculture and industry. Underwater Acoustic Sensor Networks (UASNs) is one of the important technologies for marine environmental monitoring. Therefore, it is of great significance to study the node self- localization technology of underwater acoustic sensor [...] Read more.
Groundwater is an important source of human activities, agriculture and industry. Underwater Acoustic Sensor Networks (UASNs) is one of the important technologies for marine environmental monitoring. Therefore, it is of great significance to study the node self- localization technology of underwater acoustic sensor network. This paper mainly studies the node localization algorithm based on range-free. In order to save cost and energy consumption, only a small number of sensing nodes in sensor networks usually know their own location. How to locate all nodes accurately through these few nodes is the focus of our research. In this paper, combined with the compressive sensing algorithm, a range-free node localization algorithm based on node hop information is proposed. Aiming at the problem that connection information collected by the algorithm is an integer, the hop is modified to further improve the localization performance. The simulation analysis shows that the improved algorithm is effective to improve the localization accuracy without additional cost and energy consumption compared with the traditional method. Full article
Open AccessArticle
Assessing Older Adults’ Daily Mobility: A Comparison of GPS-Derived and Self-Reported Mobility Indicators
Sensors 2019, 19(20), 4551; https://doi.org/10.3390/s19204551 - 19 Oct 2019
Viewed by 294
Abstract
Interest in global positioning system (GPS)-based mobility assessment for health and aging research is growing, and with it the demand for validated GPS-based mobility indicators. Time out of home (TOH) and number of activity locations (#ALs) are two indicators that are often derived [...] Read more.
Interest in global positioning system (GPS)-based mobility assessment for health and aging research is growing, and with it the demand for validated GPS-based mobility indicators. Time out of home (TOH) and number of activity locations (#ALs) are two indicators that are often derived from GPS data, despite lacking consensus regarding thresholds to be used to extract those as well as limited knowledge about their validity. Using 7 days of GPS and diary data of 35 older adults, we make the following three main contributions. First, we perform a sensitivity analysis to investigate how using spatial and temporal thresholds to compute TOH and #ALs affects the agreement between self-reported and GPS-based indicators. Second, we show how daily self-reported and GPS-derived mobility indicators are compared. Third, we explore whether the type and duration of self-reported activity events are related to the degree of correspondence between reported and GPS event. Highest indicator agreement was found for temporal interpolation (Tmax) of up to 5 h for both indicators, a radius (Dmax) to delineate home between 100 and 200 m for TOH, and for #ALs a spatial extent (Dmax) between 125 and 200 m, and temporal extent (Tmin) between 5 and 6 min to define an activity location. High agreement between self-reported and GPS-based indicators is obtained for TOH and moderate agreement for #ALs. While reported event type and duration impact on whether a reported event has a matching GPS event, indoor and outdoor events are detected at equal proportions. This work will help future studies to choose optimal threshold settings and will provide knowledge about the validity of mobility indicators. Full article
(This article belongs to the Special Issue Wearable Motion Sensors Applied in Older Adults)
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Open AccessArticle
An Ensemble Filter for Indoor Positioning in a Retail Store Using Bluetooth Low Energy Beacons
Sensors 2019, 19(20), 4550; https://doi.org/10.3390/s19204550 - 19 Oct 2019
Viewed by 189
Abstract
This paper has developed and deployed a Bluetooth Low Energy (BLE) beacon-based indoor positioning system in a two-floor retail store. The ultimate purpose of this study was to compare the different indoor positioning techniques towards achieving efficient position determination of moving customers in [...] Read more.
This paper has developed and deployed a Bluetooth Low Energy (BLE) beacon-based indoor positioning system in a two-floor retail store. The ultimate purpose of this study was to compare the different indoor positioning techniques towards achieving efficient position determination of moving customers in the retail store. The innovation of this research lies in its context (the retail store) and the fact that this is not a laboratory, controlled experiment. Retail stores are challenging environments with multiple sources of noise (e.g., shoppers’ moving) that impede indoor localization. To the best of the authors’ knowledge, this is the first work concerning indoor localization of consumers in a real retail store. This study proposes an ensemble filter with lower absolute mean and root mean squared errors than the random forest. Moreover, the localization error is approximately 2 m, while for the random forest, it is 2.5 m. In retail environments, even a 0.5 m deviation is significant because consumers may be positioned in front of different store shelves and, thus, different product categories. The more accurate the consumer localization, the more accurate and rich insights on the customers’ shopping behavior. Consequently, retailers can offer more effective customer location-based services (e.g., personalized offers) and, overall, better consumer localization can improve decision making in retailing. Full article
(This article belongs to the collection Positioning and Navigation)
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Open AccessArticle
Efficient Parameter Estimation for Sparse SAR Imaging Based on Complex Image and Azimuth-Range Decouple
Sensors 2019, 19(20), 4549; https://doi.org/10.3390/s19204549 - 19 Oct 2019
Viewed by 176
Abstract
Sparse signal processing theory has been applied to synthetic aperture radar (SAR) imaging. In compressive sensing (CS), the sparsity is usually considered as a known parameter. However, it is unknown practically. For many functions of CS, we need to know this parameter. Therefore, [...] Read more.
Sparse signal processing theory has been applied to synthetic aperture radar (SAR) imaging. In compressive sensing (CS), the sparsity is usually considered as a known parameter. However, it is unknown practically. For many functions of CS, we need to know this parameter. Therefore, the estimation of sparsity is crucial for sparse SAR imaging. The sparsity is determined by the size of regularization parameter. Several methods have been presented for automatically estimating the regularization parameter, and have been applied to sparse SAR imaging. However, these methods are deduced based on an observation matrix, which will entail huge computational and memory costs. In this paper, to enhance the computational efficiency, an efficient adaptive parameter estimation method for sparse SAR imaging is proposed. The complex image-based sparse SAR imaging method only considers the threshold operation of the complex image, which can reduce the computational costs significantly. By utilizing this feature, the parameter is pre-estimated based on a complex image. In order to estimate the sparsity accurately, adaptive parameter estimation is then processed in the raw data domain, combining with the pre-estimated parameter and azimuth-range decouple operators. The proposed method can reduce the computational complexity from a quadratic square order to a linear logarithm order, which can be used in the large-scale scene. Simulated and Gaofen-3 SAR data processing results demonstrate the validity of the proposed method. Full article
(This article belongs to the Section Remote Sensors, Control, and Telemetry)
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Open AccessArticle
CdTe Quantum Dots Modified with Cysteamine: A New Efficient Nanosensor for the Determination of Folic Acid
Sensors 2019, 19(20), 4548; https://doi.org/10.3390/s19204548 - 19 Oct 2019
Viewed by 173
Abstract
In this paper, we report the synthesis, characterization, and application of a new fluorescent nanosensor based on water-soluble CdTe quantum dots (QDs) coated with cysteamine (CA) for the determination of folic acid (FA). CdTe/CA QDs were characterized by high-resolution transmission electron microscopy, the [...] Read more.
In this paper, we report the synthesis, characterization, and application of a new fluorescent nanosensor based on water-soluble CdTe quantum dots (QDs) coated with cysteamine (CA) for the determination of folic acid (FA). CdTe/CA QDs were characterized by high-resolution transmission electron microscopy, the zeta potential, and Fourier-transform infrared (FT-IR), UV-visible, and fluorescence spectroscopy. CdTe QDs coated with mercaptopropionic acid (MPA) and glutathione (GSH) were prepared for comparison purposes. The effect of FA on the photoluminescence intensity of the three thiol-capped QDs at pH 8 was studied. Only CdTe/CA QDs showed a notable fluorescence quenching in the presence of FA. Then, a nanosensor based on the fluorescence quenching of the CdTe QDs at pH 8 was explored. Under optimum conditions, the calibration curve showed a linear fluorescence quenching response in a concentration range of FA from 0.16 to 16.4 μM (R2 = 0.9944), with a detection limit of 0.048 μM. A probable mechanism of fluorescence quenching was proposed. The nanosensor showed good selectivity over other possible interferences. This method has been applied for FA quantification in orange beverage samples with excellent results (recoveries from 98.3 to 103.9%). The good selectivity, sensitivity, low cost, and rapidity make CdTe /CA QDs a suitable nanosensor for FA determination. Full article
(This article belongs to the Special Issue Fluorescence-Based Sensors)
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