Sensors, Volume 14, Issue 9 (September 2014) – 118 articles , Pages 15641-17863

Fluorescence is one of the most important analytical methods used in biological studies. In the past decade or two, instrumentation in this field has greatly advanced, and now it is possible to detect single photons or fluorescent molecules [1,2], or break the Abbe diffraction limit to distinguish two points spaced less than 50 nm apart [3]. Concurrently, the development of improved fluorescent probes, which can be coupled with state-of-the-art instruments, has been equally important. This special issue on “fluorescent biosensors” in Sensors reports recent results from eight research groups in the field of sensor development. It includes three review articles, and six research articles reporting original results. [...] Full article

The purpose of this study was to improve the accuracy of real-time ego-motion tracking through inertial sensor and vision sensor fusion. Due to low sampling rates supported by web-based vision sensor and accumulation of errors in inertial sensors, ego-motion tracking with vision sensors is commonly afflicted by slow updating rates, while motion tracking with inertial sensor suffers from rapid deterioration in accuracy with time. This paper starts with a discussion of developed algorithms for calibrating two relative rotations of the system using only one reference image. Next, stochastic noises associated with the inertial sensor are identified using Allan Variance analysis, and modeled according to their characteristics. Finally, the proposed models are incorporated into an extended Kalman filter for inertial sensor and vision sensor fusion. Compared with results from conventional sensor fusion models, we have shown that ego-motion tracking can be greatly enhanced using the proposed error correction model. Full article

We theoretically demonstrate a low crosstalk ring-slot array structure used for label-free multiplexed sensing. The proposed sensors array is based on an array of three ring-slot and input/output line defect coupling waveguides. Each ring-slot cavity has slightly different cavity spacing and different resonant frequency. Results obtained using two dimensional finite-difference time-domain (2D-FDTD) simulation indicate that the resonant frequencies of each sensor unit in response to the refractive index variations are independent. The refractive index sensitivity is 134 ~ 145.5 nm/RIU (refractive index unit) and the Q factors more than 10⁴ can be achieved. The calculated detect limit lower than 1.13 × 10⁻⁴ RIU is obtained. In addition, an extremely small crosstalk lower than −25.8 dB is achieved among the array of three ring-slot cavities. The results demonstrate that this multiplexed sensor array is a promising platform for integrated optical devices and enables highly parallel label-free detection. Full article

Automatic Guided Vehicles (AGVs) are navigated utilising multiple types of sensors for detecting the environment. In this investigation such sensors are replaced and/or minimized by the use of a single omnidirectional camera picture stream. An area of interest is extracted, and by using image processing the vehicle is navigated on a set path. Reconfigurability is added to the route layout by signs incorporated in the navigation process. The result is the possible manipulation of a number of AGVs, each on its own designated colour-signed path. This route is reconfigurable by the operator with no programming alteration or intervention. A low resolution camera and a Matlab^® software development platform are utilised. The use of Matlab^® lends itself to speedy evaluation and implementation of image processing options on the AGV, but its functioning in such an environment needs to be assessed. Full article

The Internet of Things (IoT) has inspired solutions that are already available for addressing problems in various application scenarios, such as healthcare, security, emergency support and tourism. However, there is no clear approach to modeling these systems and envisioning their capabilities at the design time. Therefore, the process of designing these systems is ad hoc and its real impact is evaluated once the solution is already implemented, which is risky and expensive. This paper proposes a modeling approach that uses human-centric wireless sensor networks to specify and evaluate models of IoT-based systems at the time of design, avoiding the need to spend time and effort on early implementations of immature designs. It allows designers to focus on the system design, leaving the implementation decisions for a next phase. The article illustrates the usefulness of this proposal through a running example, showing the design of an IoT-based solution to support the first responses during medium-sized or large urban incidents. The case study used in the proposal evaluation is based on a real train crash. The proposed modeling approach can be used to design IoT-based systems for other application scenarios, e.g., to support security operatives or monitor chronic patients in their homes. Full article

This paper concerns the development of an immunosensor for detection of peptides derived from avian influenza hemagglutinin H5. Its preparation consists of successive gold electrode modification steps: (i) modification with 1,6-hexanedithiol and gold colloidal nanoparticles; (ii) immobilization of antibody-binding fragments (Fab’) of anti-hemagglutinin H5 monoclonal antibodies Mab 6-9-1 via S-Au covalent bonds; and (iii) covering the remaining free space on the electrode surfaces with bovine serum albumin. The interactions between Fab’ fragments and hemagglutinin (HA) variants have been explored with electrochemical impedance spectroscopy (EIS) in the presence of [Fe(CN)₆]^3−/4− as an electroactive marker. The immunosensor was able to recognize three different His-tagged variants of recombinant hemagglutinin from H5N1 viruses: H1 subunit (17–340 residues) of A/swan/Poland/305-135V08/2006, the long HA (17–530 residues) A/Bar-headed Goose/Qinghai/12/2005 and H1 subunit (1–345 residues) of A/Vietnam/1194/2004. The strongest response has been observed for the long variant with detection limit of 2.2 pg/mL and dynamic range from 4.0 to 20.0 pg/mL. Full article

We address the problem of acquiring and transmitting EEG signals in Wireless Body Area Networks (WBAN) in an energy efficient fashion. In WBANs, the energy is consumed by three operations: sensing (sampling), processing and transmission. Previous studies only addressed the problem of reducing the transmission energy. For the first time, in this work, we propose a technique to reduce sensing and processing energy as well: this is achieved by randomly under-sampling the EEG signal. We depart from previous Compressed Sensing based approaches and formulate signal recovery (from under-sampled measurements) as a matrix completion problem. A new algorithm to solve the matrix completion problem is derived here. We test our proposed method and find that the reconstruction accuracy of our method is significantly better than state-of-the-art techniques; and we achieve this while saving sensing, processing and transmission energy. Simple power analysis shows that our proposed methodology consumes considerably less power compared to previous CS based techniques. Full article

This paper presents two PDMS photonic biosensor designs that can be used for continuous monitoring of glucose concentrations. The first design, the internally immobilized sensor, consists of a reactor chamber, micro-lenses and self-alignment structures for fiber optics positioning. This sensor design allows optical detection of glucose concentrations under continuous glucose flow conditions of 33 µL/h based on internal co-immobilization of glucose oxidase (GOX) and horseradish peroxidase (HRP) on the internal PDMS surface of the reactor chamber. For this design, two co-immobilization methods, the simple adsorption and the covalent binding (PEG) methods were tested. Experiments showed successful results when using the covalent binding (PEG) method, where glucose concentrations up to 5 mM with a coefficient of determination (R²) of 0.99 and a limit of detection of 0.26 mM are detectable. The second design is a modified version of the internally immobilized sensor, where a microbead chamber and a beads filling channel are integrated into the sensor. This modification enabled external co-immobilization of enzymes covalently onto functionalized silica microbeads and allows binding a huge amount of HRP and GOX enzymes on the microbeads surfaces which increases the interaction area between immobilized enzymes and the analyte. This has a positive effect on the amount and rate of chemical reactions taking place inside the chamber. The sensor was tested under continuous glucose flow conditions and was found to be able to detect glucose concentrations up to 10 mM with R² of 0.98 and a limit of detection of 0.7 mM. Such results are very promising for the application in photonic LOC systems used for online analysis. Full article

Wireless Sensor Networks (WSNs) consist of hundreds or thousands of sensor nodes with limited processing, storage, and battery capabilities. There are several strategies to reduce the power consumption of WSN nodes (by increasing the network lifetime) and increase the reliability of the network (by improving the WSN Quality of Service). However, there is an inherent conflict between power consumption and reliability: an increase in reliability usually leads to an increase in power consumption. For example, routing algorithms can send the same packet though different paths (multipath strategy), which it is important for reliability, but they significantly increase the WSN power consumption. In this context, this paper proposes a model for evaluating the reliability of WSNs considering the battery level as a key factor. Moreover, this model is based on routing algorithms used by WSNs. In order to evaluate the proposed models, three scenarios were considered to show the impact of the power consumption on the reliability of WSNs. Full article

Along with the dose rate and the total irradiation dose measurements, the knowledge of the beam localization and the beam profile/energy distribution in the beam are parameters of interest for charged particle accelerator installations when they are used in scientific investigations, industrial applications or medical treatments. The transverse profile of the beam, its position, its centroid location, and its focus or flatness depend on the instrument operating conditions or on the beam exit setup. Proof-of-concept of a new type of charged particle beam diagnostics based on fiber Bragg gratings (FBGs) was demonstrated. Its operating principle relies on the measurement of the peak wavelength changes for an array of FBG sensors as function of the temperature following the exposure to an electron beam. Periodically, the sensor irradiation is stopped and the FBG are force cooled to a reference temperature with which the temperature influencing each sensor during beam exposure is compared. Commercially available FBGs, and FBGs written in radiation resistant optical fibers, were tested under electron beam irradiation in order to study their possible use in this application. Full article

Experimental work on the synthesis of the CoSb₂O₆ oxide and its CO₂ sensing properties is presented here. The oxide was synthesized by a microwave-assisted colloidal method in presence of ethylenediamine after calcination at 600 °C. This CoSb₂O₆ oxide crystallized in a tetragonal structure with cell parameters and Å, and space group P4₂/mnm. To prove its physical, chemical and sensing properties, the oxide was subjected to a series of tests: Raman spectroscopy, Scanning Electron Microscopy (SEM) and impedance (Z) measurements. Microstructures, like columns, bars and hollow hemispheres, were observed. For the CO₂ sensing test, a thick film of CoSb₂O₆ was used, measuring the impedance variations on the presence of air/CO₂ flows (0.100 sccm/0.100 sccm) using AC (alternating current) signals in the frequency-range 0.1–100 kHz and low relative temperatures (250 and 300 °C). The CO₂ sensing results were quite good. Full article

This paper describes a sensor dedicated to measuring the vertical profile of the complex permittivity and the temperature of any medium in which sensor electrodes are inserted. Potential applications are the estimate of the humidity and salinity in a porous medium, such as a soil. It consists of vertically-stacked capacitors along two conductive parallel cylinders of 5 cm in diameter and at a 10-cm distance to scan a significant volume of the medium (~1 L). It measures their admittances owing to a self-balanced impedance bridge operating at a frequency in the range of 1–20 MHz, possibly 30 MHz. Thanks to accurate design and electronic circuit theory-based modeling, the determination of the admittances takes into account all distortions due to lead and bridge electromagnetic effects inside the sensor when working at high frequencies. Calibration procedures and uncertainties are presented. The article also describes developments to make the present sensor autonomous on digital acquisition, basic data treatment and energy, as well as able to transfer stored data by a radio link. These steps in progress are prerequisites for a wireless network of sensors. Full article

In this study, the construction and test of tapered plastic optical fiber (POF) sensors, based on an intensity modulation approach are described. Tapered fiber sensors with different diameters of 0.65 mm, 0.45 mm, and 0.35 mm, were used to measure various concentrations of Remazol black B (RBB) dye aqueous solutions at room temperature. The concentrations of the RBB solutions were varied from 0 ppm to 70 ppm. In addition, the effect of varying the temperature of the RBB solution was also investigated. In this case, the output of the sensor was measured at four different temperatures of 27 °C, 30 °C, 35 °C, and 40 °C, while its concentration was fixed at 50 ppm and 100 ppm. The experimental results show that the tapered POF with d = 0.45 mm achieves the best performance with a reasonably good sensitivity of 61 × 10⁻⁴ and a linearity of more than 99%. It also maintains a sufficient and stable signal when heat was applied to the solution with a linearity of more than 97%. Since the transmitted intensity is dependent on both the concentration and temperature of the analyte, multiple linear regression analysis was performed to combine the two independent variables into a single equation. The resulting equation was then validated experimentally and the best agreement between the calculated and experimental results was achieved by the sensor with d = 0.45 mm, where the minimum discrepancy is less than 5%. The authors conclude that POF-based sensors are suitable for RBB dye concentration sensing and, with refinement in fabrication, better results could be achieved. Their low fabrication cost, simple configuration, accuracy, and high sensitivity would attract many potential applications in chemical and biological sensing. Full article

This study compared the responses of Pd-functionalized and pristine titanate (TiO₂) nanotube arrays to ethanol with those to acetone to determine the effects of functionalization of TiO₂ nanotubes with Pd nanoparticles on the sensitivity and selectivity. The responses of pristine and Pd-functionalized TiO₂ nanotube arrays to ethanol gas at 200 °C were ~2877% and ~21,253%, respectively. On the other hand, the responses of pristine and Pd-functionalized TiO₂ nanotube arrays to acetone gas at 250 °C were ~1636% and 8746% respectively. In the case of ethanol sensing, the response and recovery times of Pd-functionalized TiO₂ nanotubes (10.2 and 7.1 s) were obviously shorter than those of pristine TiO₂ nanotubes (14.3 and 8.8 s), respectively. In contrast, in the case of acetone sensing the response and recovery times of Pd-functionalized TiO₂ nanotubes (42.5 and 19.7 s) were almost the same as those of pristine TiO₂ nanotubes (47.2 and 17.9 s). TiO₂ nanotube arrays showed the strongest response to ethanol and Pd functionalization was the most effective in improving the response of TiO₂ nanotubes to ethanol among six different types of gases: ethanol, acetone, CO, H₂, NH₃ and NO₂. The origin of the superior sensing properties of Pd-functionalized TiO₂ nanotubes toward ethanol to acetone is also discussed. Full article

In this paper we discuss the design and evaluation of a mobile based tool to collect activity data on a large scale. The current approach, based on an existing activity recognition module, recognizes class transitions from a set of specific activities (for example walking and running) to the standing still activity. Once this transition is detected the system prompts the user to provide a label for their previous activity. This label, along with the raw sensor data, is then stored locally prior to being uploaded to cloud storage. The system was evaluated by ten users. Three evaluation protocols were used, including a structured, semi-structured and free living protocol. Results indicate that the mobile application could be used to allow the user to provide accurate ground truth labels for their activity data. Similarities of up to 100% where observed when comparing the user prompted labels and those from an observer during structured lab based experiments. Further work will examine data segmentation and personalization issues in order to refine the system. Full article

This paper presents a new micropower analog lock-in amplifier (LIA) suitable for battery-operated applications thanks to its reduced size and power consumption as well as its operation with single-supply voltage. The proposed LIA was designed in a 0.18 µm CMOS process with a single supply voltage of 1.8 V. Experimental results show a variable DC gain ranging from 24.7 to 42 dB, power consumption of 417 µW and integration area of 0.013 mm². The LIA performance was demonstrated by measuring carbon monoxide concentrations as low as 1 ppm in dry N₂. The experimental results show that the response to CO of the sensing system can be considerably improved by means of the proposed LIA. Full article

The World Health Organization estimates that 100 thousand people in the world die every year from asbestos-related cancers and more than 300 thousand European citizens are expected to die from asbestos-related mesothelioma by 2030. Both the European and the Italian legislations have banned the manufacture, importation, processing and distribution in commerce of asbestos-containing products and have recommended action plans for the safe removal of asbestos from public and private buildings. This paper describes the quantitative mapping of asbestos-cement covers over a large mountainous region of Italian Western Alps using the Multispectral Infrared and Visible Imaging Spectrometer sensor. A very large data set made up of 61 airborne transect strips covering 3263 km² were processed to support the identification of buildings with asbestos-cement roofing, promoted by the Valle d’Aosta Autonomous Region with the support of the Regional Environmental Protection Agency. Results showed an overall mapping accuracy of 80%, in terms of asbestos-cement surface detected. The influence of topography on the classification’s accuracy suggested that even in high relief landscapes, the spatial resolution of data is the major source of errors and the smaller asbestos-cement covers were not detected or misclassified. Full article

Soft rot is a commonly occurring potato tuber disease that each year causes substantial losses to the food industry. Here, we explore the possibility of early detection of the disease via gas/vapor analysis, in a laboratory environment, using a recent technology known as FAIMS (Field Asymmetric Ion Mobility Spectrometry). In this work, tubers were inoculated with a bacterium causing the infection, Pectobacterium carotovorum, and stored within set environmental conditions in order to manage disease progression. They were compared with controls stored in the same conditions. Three different inoculation time courses were employed in order to obtain diseased potatoes showing clear signs of advanced infection (for standard detection) and diseased potatoes with no apparent evidence of infection (for early detection). A total of 156 samples were processed by PCA (Principal Component Analysis) and k-means clustering. Results show a clear discrimination between controls and diseased potatoes for all experiments with no difference among observations from standard and early detection. Further analysis was carried out by means of a statistical model based on LDA (Linear Discriminant Analysis) that showed a high classification accuracy of 92.1% on the test set, obtained via a LOOCV (leave-one out cross-validation). Full article

Clinical scores and motion-capturing gait analysis are today’s gold standard for outcome measurement after knee arthroplasty, although they are criticized for bias and their ability to reflect patients’ actual quality of life has been questioned. In this context, mobile gait analysis systems have been introduced to overcome some of these limitations. This study used a previously developed mobile gait analysis system comprising three inertial sensor units to evaluate daily activities and sports. The sensors were taped to the lumbosacral junction and the thigh and shank of the affected limb. The annotated raw data was evaluated using our validated proprietary software. Six patients undergoing knee arthroplasty were examined the day before and 12 months after surgery. All patients reported a satisfactory outcome, although four patients still had limitations in their desired activities. In this context, feasible running speed demonstrated a good correlation with reported impairments in sports-related activities. Notably, knee flexion angle while descending stairs and the ability to stop abruptly when running exhibited good correlation with the clinical stability and proprioception of the knee. Moreover, fatigue effects were displayed in some patients. The introduced system appears to be suitable for outcome measurement after knee arthroplasty and has the potential to overcome some of the limitations of stationary gait labs while gathering additional meaningful parameters regarding the force limits of the knee. Full article

An amperometric magneto-immunosensor (AMIS) for the detection of residues of fluoroquinolone antibiotics in milk samples is described for the first time. The immunosensor presented combines magnetic beads biomodified with an antibody with a broad recognition profile of fluoroquinolones, a haptenized enzyme and a magnetic graphite–epoxy composite (m-GEC) electrode. After the immunochemical reaction with specific enzyme tracer, the antibody biomodified magnetic beads are easily captured by an electrode made of graphite-epoxy composite containing a magnet, which also acts as transducer for the electrochemical detection. In spite of the complexity of milk, the use of magnetic beads allows elimination of potential interferences caused by the matrix components; hence the AMIS could perform quantitative measurements, directly in these samples, without any additional sample cleanup or extraction step. The immunosensor is able to detect up to seven different fluoroquinolones far below the MRLs defined by the UE for milk; for example ciprofloxacin is detected directly in milk with an IC₅₀ of 0.74 µg/L and a LOD of 0.009 µg/L. This strategy offers great promise for rapid, simple, cost-effective, and on-site analysis fluoroquinolones in complex samples. Full article

This article discusses the experiences from the development and deployment of two image-based environmental monitoring sensor applications using an embedded wireless sensor network. Our system uses low-power image sensors and the Tenet general purpose sensing system for tiered embedded wireless sensor networks. It leverages Tenet’s built-in support for reliable delivery of high rate sensing data, scalability and its flexible scripting language, which enables mote-side image compression and the ease of deployment. Our first deployment of a pitfall trap monitoring application at the James San Jacinto Mountain Reserve provided us with insights and lessons learned into the deployment of and compression schemes for these embedded wireless imaging systems. Our three month-long deployment of a bird nest monitoring application resulted in over 100,000 images collected from a 19-camera node network deployed over an area of 0.05 square miles, despite highly variable environmental conditions. Our biologists found the on-line, near-real-time access to images to be useful for obtaining data on answering their biological questions. Full article

Gyroscopes based on micro-electromechanical system (MEMS) technology suffer in high-dynamic applications due to obvious g-sensitivity errors. These errors can induce large biases in the gyroscope, which can directly affect the accuracy of attitude estimation in the integration of the inertial navigation system (INS) and the Global Positioning System (GPS). The observability determines the existence of solutions for compensating them. In this paper, we investigate the observability of the INS/GPS system with consideration of the g-sensitivity errors. In terms of two types of g-sensitivity coefficients matrix, we add them as estimated states to the Kalman filter and analyze the observability of three or nine elements of the coefficient matrix respectively. A global observable condition of the system is presented and validated. Experimental results indicate that all the estimated states, which include position, velocity, attitude, gyro and accelerometer bias, and g-sensitivity coefficients, could be made observable by maneuvering based on the conditions. Compared with the integration system without compensation for the g-sensitivity errors, the attitude accuracy is raised obviously. Full article

In this paper, a spectroscopic sensor formed by a silicon-on-insulator waveguiding Bragg grating ring resonator working in linear and non-linear regime is proposed. In linear regime, the device shows a spectral response characterized by a photonic band gap (PBG). Very close to the band gap edges, the resonant structure exhibits split modes having a splitting magnitude equal to the PBG spectral extension, whose characteristics can be exploited to obtain a RI optical sensor almost insensitive to the fabrication tolerances and environmental perturbations. When the device operates in nonlinear regime, exactly in the spectral region showing the split resonant modes, the RI sensing performance is strongly improved with respect to the linear regime. This improvement, demonstrated by taking into account all the non-linear effects excited in the integrated silicon structure (i.e., Two Photon Absorption (TPA), TPA-induced Free Carrier Absorption, plasma dispersion, Self-Phase-Modulation and Cross-Phase-Modulation effects as induced by Kerr nonlinearity) as well as the deleterious thermal and stress effects, allows enhancing the performance of the RI split mode resonant sensors, while achieving good immunity to the fabrication tolerances and environmental perturbations. The improvement in terms of sensor resolution can be at least one order of magnitude, still without using optimal parameters. Full article

We propose a temperature sensor design based on surface plasmon resonances (SPRs) supported by filling the holes of a six-hole photonic crystal fiber (PCF) with a silver nanowire. A liquid mixture (ethanol and chloroform) with a large thermo-optic coefficient is filled into the PCF holes as sensing medium. The filled silver nanowires can support resonance peaks and the peak will shift when temperature variations induce changes in the refractive indices of the mixture. By measuring the peak shift, the temperature change can be detected. The resonance peak is extremely sensitive to temperature because the refractive index of the filled mixture is close to that of the PCF material. Our numerical results indicate that a temperature sensitivity as high as 4 nm/K can be achieved and that the most sensitive range of the sensor can be tuned by changing the volume ratios of ethanol and chloroform. Moreover, the maximal sensitivity is relatively stable with random filled nanowires, which will be very convenient for the sensor fabrication. Full article

A constant false alarm rate (CFAR) target detector in non-homogenous backgrounds is proposed. Based on K-sample Anderson-Darling (AD) tests, the method re-arranges the reference cells by merging homogenous sub-blocks surrounding the cell under test (CUT) into a new reference window to estimate the background statistics. Double partition test, clutter edge refinement and outlier elimination are used as an anti-clutter processor in the proposed Modified AD (MAD) detector. Simulation results show that the proposed MAD test based detector outperforms cell-averaging (CA) CFAR, greatest of (GO) CFAR, smallest of (SO) CFAR, order-statistic (OS) CFAR, variability index (VI) CFAR, and CUT inclusive (CI) CFAR in most non-homogenous situations. Full article

The calibration of micro inertial measurement units is important in ensuring the precision of navigation systems, which are equipped with microelectromechanical system sensors that suffer from various errors. However, traditional calibration methods cannot meet the demand for fast field calibration. This paper presents a fast field calibration method based on the Powell algorithm. As the key points of this calibration, the norm of the accelerometer measurement vector is equal to the gravity magnitude, and the norm of the gyro measurement vector is equal to the rotational velocity inputs. To resolve the error parameters by judging the convergence of the nonlinear equations, the Powell algorithm is applied by establishing a mathematical error model of the novel calibration. All parameters can then be obtained in this manner. A comparison of the proposed method with the traditional calibration method through navigation tests shows the classic performance of the proposed calibration method. The proposed calibration method also saves more time compared with the traditional calibration method. Full article

A dynamic attitude measurement system (DAMS) is developed based on a laser inertial navigation system (LINS). Three factors of the dynamic attitude measurement error using LINS are analyzed: dynamic error, time synchronization and phase lag. An optimal coning errors compensation algorithm is used to reduce coning errors, and two-axis wobbling verification experiments are presented in the paper. The tests indicate that the attitude accuracy is improved 2-fold by the algorithm. In order to decrease coning errors further, the attitude updating frequency is improved from 200 Hz to 2000 Hz. At the same time, a novel finite impulse response (FIR) filter with three notches is designed to filter the dither frequency of the ring laser gyro (RLG). The comparison tests suggest that the new filter is five times more effective than the old one. The paper indicates that phase-frequency characteristics of FIR filter and first-order holder of navigation computer constitute the main sources of phase lag in LINS. A formula to calculate the LINS attitude phase lag is introduced in the paper. The expressions of dynamic attitude errors induced by phase lag are derived. The paper proposes a novel synchronization mechanism that is able to simultaneously solve the problems of dynamic test synchronization and phase compensation. A single-axis turntable and a laser interferometer are applied to verify the synchronization mechanism. The experiments results show that the theoretically calculated values of phase lag and attitude error induced by phase lag can both match perfectly with testing data. The block diagram of DAMS and physical photos are presented in the paper. The final experiments demonstrate that the real-time attitude measurement accuracy of DAMS can reach up to 20″ (1σ) and the synchronization error is less than 0.2 ms on the condition of three axes wobbling for 10 min. Full article

A linearized wavelength-swept thermo-optic laser chip was applied to demonstrate a fiber Bragg grating (FBG) sensor interrogation system. A broad tuning range of 11.8 nm was periodically obtained from the laser chip for a sweep rate of 16 Hz. To measure the linear time response of the reflection signal from the FBG sensor, a programmed driving signal was directly applied to the wavelength-swept laser chip. The linear wavelength response of the applied strain was clearly extracted with an R-squared value of 0.99994. To test the feasibility of the system for dynamic measurements, the dynamic strain was successfully interrogated with a repetition rate of 0.2 Hz by using this FBG sensor interrogation system. Full article

The objective of the present study was to deal with the rotordynamics of the rotor of an ultra-high speed PM type synchronous motor-generator for a 500 W rated micro gas turbine generator. This paper introduces dynamic analysis, and experiments on the motor-generator. The focus is placed on an analytical approach considering the mechanical dynamic problems. It is essential to deal with dynamic stability at ultra-high speeds. Unbalance response analysis is performed by calculating the unbalance with and without balancing using a balancing machine. Critical speed analysis is performed to determine the operating speed with sufficient separation margin. The unbalance response analysis is compared with the experimental results considering the balancing grade (ISO 1940-1) and predicted vibration displacement with and without balancing. Based on these results, a high-speed motor-generator was successfully developed. Full article

White blood cell (WBC) segmentation, which is important for cytometry, is a challenging issue because of the morphological diversity of WBCs and the complex and uncertain background of blood smear images. This paper proposes a novel method for the nucleus and cytoplasm segmentation of WBCs for cytometry. A color adjustment step was also introduced before segmentation. Color space decomposition and k-means clustering were combined for segmentation. A database including 300 microscopic blood smear images were used to evaluate the performance of our method. The proposed segmentation method achieves 95.7% and 91.3% overall accuracy for nucleus segmentation and cytoplasm segmentation, respectively. Experimental results demonstrate that the proposed method can segment WBCs effectively with high accuracy. Full article

This study presents an optical inspection system for detecting a commercial point-of-care testing product and a new detection model covering from qualitative to quantitative analysis. Human chorionic gonadotropin (hCG) strips (cut-off value of the hCG commercial product is 25 mIU/mL) were the detection target in our study. We used a complementary metal-oxide semiconductor (CMOS) sensor to detect the colors of the test line and control line in the specific strips and to reduce the observation errors by the naked eye. To achieve better linearity between the grayscale and the concentration, and to decrease the standard deviation (increase the signal to noise ratio, S/N), the Taguchi method was used to find the optimal parameters for the optical inspection system. The pregnancy test used the principles of the lateral flow immunoassay, and the colors of the test and control line were caused by the gold nanoparticles. Because of the sandwich immunoassay model, the color of the gold nanoparticles in the test line was darkened by increasing the hCG concentration. As the results reveal, the S/N increased from 43.48 dB to 53.38 dB, and the hCG concentration detection increased from 6.25 to 50 mIU/mL with a standard deviation of less than 10%. With the optimal parameters to decrease the detection limit and to increase the linearity determined by the Taguchi method, the optical inspection system can be applied to various commercial rapid tests for the detection of ketamine, troponin I, and fatty acid binding protein (FABP). Full article

This paper presents a monocular visual odometry algorithm that incorporates a wheeled vehicle model for ground vehicles. The main innovation of this algorithm is to use the single-track bicycle model to interpret the relationship between the yaw rate and side slip angle, which are the two most important parameters that describe the motion of a wheeled vehicle. Additionally, the pitch angle is also considered since the planar-motion hypothesis often fails due to the dynamic characteristics of wheel suspensions and tires in real-world environments. Linearization is used to calculate a closed-form solution of the motion parameters that works as a hypothesis generator in a RAndom SAmple Consensus (RANSAC) scheme to reduce the complexity in solving equations involving trigonometric. All inliers found are used to refine the winner solution through minimizing the reprojection error. Finally, the algorithm is applied to real-time on-board visual localization applications. Its performance is evaluated by comparing against the state-of-the-art monocular visual odometry methods using both synthetic data and publicly available datasets over several kilometers in dynamic outdoor environments. Full article

Activity recognition for the purposes of recognizing a user’s intentions using multimodal sensors is becoming a widely researched topic largely based on the prevalence of the smartphone. Previous studies have reported the difficulty in recognizing life-logs by only using a smartphone due to the challenges with activity modeling and real-time recognition. In addition, recognizing life-logs is difficult due to the absence of an established framework which enables the use of different sources of sensor data. In this paper, we propose a smartphone-based Hierarchical Activity Recognition Framework which extends the Naïve Bayes approach for the processing of activity modeling and real-time activity recognition. The proposed algorithm demonstrates higher accuracy than the Naïve Bayes approach and also enables the recognition of a user’s activities within a mobile environment. The proposed algorithm has the ability to classify fifteen activities with an average classification accuracy of 92.96%. Full article

In this work, we decided to apply a hierarchical weighted decision, proposed and used in other research fields, for the recognition of gait phases. The developed and validated novel distributed classifier is based on hierarchical weighted decision from outputs of scalar Hidden Markov Models (HMM) applied to angular velocities of foot, shank, and thigh. The angular velocities of ten healthy subjects were acquired via three uni-axial gyroscopes embedded in inertial measurement units (IMUs) during one walking task, repeated three times, on a treadmill. After validating the novel distributed classifier and scalar and vectorial classifiers-already proposed in the literature, with a cross-validation, classifiers were compared for sensitivity, specificity, and computational load for all combinations of the three targeted anatomical segments. Moreover, the performance of the novel distributed classifier in the estimation of gait variability in terms of mean time and coefficient of variation was evaluated. The highest values of specificity and sensitivity (>0.98) for the three classifiers examined here were obtained when the angular velocity of the foot was processed. Distributed and vectorial classifiers reached acceptable values (>0.95) when the angular velocity of shank and thigh were analyzed. Distributed and scalar classifiers showed values of computational load about 100 times lower than the one obtained with the vectorial classifier. In addition, distributed classifiers showed an excellent reliability for the evaluation of mean time and a good/excellent reliability for the coefficient of variation. In conclusion, due to the better performance and the small value of computational load, the here proposed novel distributed classifier can be implemented in the real-time application of gait phases recognition, such as to evaluate gait variability in patients or to control active orthoses for the recovery of mobility of lower limb joints. Full article

Research on smart environments saturated with ubiquitous computing devices is rapidly advancing while raising serious privacy issues. According to recent studies, privacy concerns significantly hinder widespread adoption of smart home technologies. Previous work has shown that it is possible to infer the activities of daily living within environments equipped with wireless sensors by monitoring radio fingerprints and traffic patterns. Since data encryption cannot prevent privacy invasions exploiting transmission pattern analysis and statistical inference, various methods based on fake data generation for concealing traffic patterns have been studied. In this paper, we describe an energy-efficient, light-weight, low-latency algorithm for creating dummy activities that are semantically similar to the observed phenomena. By using these cloaking activities, the amount of fake data transmissions can be flexibly controlled to support a trade-off between energy efficiency and privacy protection. According to the experiments using real data collected from a smart home environment, our proposed method can extend the lifetime of the network by more than 2× compared to the previous methods in the literature. Furthermore, the activity cloaking method supports low latency transmission of real data while also significantly reducing the accuracy of the wireless snooping attacks. Full article

The alcoholic fermentation of Savatiano must variety was initiated under laboratory conditions and monitored daily with a gas sensor array without any pre-treatment steps. The sensor array consisted of eight interdigitated chemocapacitors (IDCs) coated with specific polymers. Two batches of fermented must were tested and also subjected daily to standard chemical analysis. The chemical composition of the two fermenting musts differed from day one of laboratory monitoring (due to different storage conditions of the musts) and due to a deliberate increase of the acetic acid content of one of the musts, during the course of the process, in an effort to spoil the fermenting medium. Sensor array responses to the headspace of the fermenting medium were compared with those obtained either for pure or contaminated samples with controlled concentrations of standard ethanol solutions of impurities. Results of data processing with Principal Component Analysis (PCA), demonstrate that this sensing system could discriminate between a normal and a potential spoiled grape must fermentation process, so this gas sensing system could be potentially applied during wine production as an auxiliary qualitative control instrument. Full article

The bitterness of bitter substances can be measured by the change in the membrane electric potential caused by adsorption (CPA) using a taste sensor (electronic tongue). In this study, we examined the relationship between the CPA value due to an acidic bitter substance and the amount of the bitter substance adsorbed onto lipid/polymer membranes, which contain different lipid contents, used in the taste sensor. We used iso-α-acid which is an acidic bitter substance found in several foods and beverages. The amount of adsorbed iso-α-acid, which was determined by spectroscopy, showed a maximum at the lipid concentration 0.1 wt % of the membrane, and the same phenomenon was observed for the CPA value. At the higher lipid concentration, however, the amount adsorbed decreased and then remained constant, while the CPA value decreased monotonically to zero. This constant adsorption amount was observed when the membrane potential in the reference solution did not change with increasing lipid concentration. The decrease in CPA value in spite of the constant adsorption amount is caused by a decrease in the sensitivity of the membrane as the surface charge density increases. The reason why the peaks appeared in both the CPA value and adsorption amount is based on the contradictory adsorption properties of iso-α-acid. The increasing charged lipid concentration of the membrane causes an increasing electrostatic attractive interaction between iso-α-acid and the membrane, but simultaneously causes a decreasing hydrophobic interaction that results in decreasing adsorption of iso-α-acid, which also has hydrophobic properties, onto the membrane. Estimates of the amount of adsorption suggest that iso-α-acid molecules are adsorbed onto both the surface and interior of the membrane. Full article

In this study, we investigate the keys to obtain a sensitive ammonia sensor with high air stability by using a low-cost polythiophene diode with a vertical channel and a porous top electrode. Poly(3-hexylthiophene) (P3HT) and air-stable poly(5,5'-bis(3-dodecyl-2-thienyl)-2,2'-bithiophene) (PQT-12) are both evaluated as the active sensing layer. Two-dimensional current simulation reveals that the proposed device exhibits numerous connected vertical nanometer junctions (VNJ). Due to the de-doping reaction between ammonia molecules and the bulk current flowing through the vertical channel, both PQT-12 and P3HT VNJ-diodes exhibit detection limits of 50-ppb ammonia. The P3HT VNJ-diode, however, becomes unstable after being stored in air for two days. On the contrary, the PQT-12 VNJ-diode keeps an almost unchanged response to 50-ppb ammonia after being stored in air for 25 days. The improved storage lifetime of an organic-semiconductor-based gas sensor in air is successfully demonstrated. Full article

In the application of a micro-/nano-mechanical resonator, the position of an accreted particle and the resonant frequencies are measured by two different physical systems. Detecting the particle position sometimes can be extremely difficult or even impossible, especially when the particle is as small as an atom or a molecule. Using the resonant frequencies to determine the mass and position of an accreted particle formulates an inverse problem. The Dirac delta function and Galerkin method are used to model and formulate an eigenvalue problem of a beam with an accreted particle. An approximate method is proposed by ignoring the off-diagonal elements of the eigenvalue matrix. Based on the approximate method, the mass and position of an accreted particle can be decoupled and uniquely determined by measuring at most three resonant frequencies. The approximate method is demonstrated to be very accurate when the particle mass is small, which is the application scenario for much of the mass sensing of micro-/nano-mechanical resonators. By solving the inverse problem, the position measurement becomes unnecessary, which is of some help to the mass sensing application of a micro-/nano-mechanical resonator by reducing two measurement systems to one. How to apply the method to the general scenario of multiple accreted particles is also discussed. Full article

In order to make conductors with large cross sections for low impedance radio frequency (RF) electronics, while still retaining high stretchability, liquid-alloy-based microfluidic stretchable electronics offers stretchable electronic systems the unique opportunity to combine various sensors on our bodies or organs with high-quality wireless communication with the external world (devices/systems), without sacrificing enhanced user comfort. This microfluidic approach, based on printed circuit board technology, allows large area processing of large cross section conductors and robust contacts, which can handle a lot of stretching between the embedded rigid active components and the surrounding system. Although it provides such benefits, further development is needed to realize its potential as a high throughput, cost-effective process technology. In this paper, tape transfer printing is proposed to supply a rapid prototyping batch process at low cost, albeit at a low resolution of 150 μm. In particular, isolated patterns can be obtained in a simple one-step process. Finally, a stretchable radio frequency identification (RFID) tag is demonstrated. The measured results show the robustness of the hybrid integrated system when the tag is stretched at 50% for 3000 cycles. Full article

A new method for dynamic measurement of deflections of the vertical (DOV) is proposed in this paper. The integration of an inertial navigation system (INS) and global navigation satellite system (GNSS) is constructed to measure the body’s attitude with respect to the astronomical coordinates. Simultaneously, the attitude with respect to the geodetic coordinates is initially measured by a star sensor under quasi-static condition and then maintained by the laser gyroscope unit (LGU), which is composed of three gyroscopes in the INS, when the vehicle travels along survey lines. Deflections of the vertical are calculated by using the difference between the attitudes with respect to the geodetic coordinates and astronomical coordinates. Moreover, an algorithm for removing the trend error of the vertical deflections is developed with the aid of Earth Gravitational Model 2008 (EGM2008). In comparison with traditional methods, the new method required less accurate GNSS, because the dynamic acceleration calculation is avoided. The errors of inertial sensors are well resolved in the INS/GNSS integration, which is implemented by a Rauch–Tung–Striebel (RTS) smoother. In addition, a single-axis indexed INS is adopted to improve the observability of the system errors and to restrain the inertial sensor errors. The proposed method is validated by Monte Carlo simulations. The results show that deflections of the vertical can achieve a precision of better than 1″ for a single survey line. The proposed method can be applied to a gravimetry system based on a ground vehicle or ship with a speed lower than 25 m/s. Full article

An oxygen gas microsensor based on nanostructured sol-gel TiO₂ thin films with a buried Pd layer was developed on a silicon substrate. The nanostructured titania thin films for O₂ sensors were prepared by the sol-gel process and became anatase after heat treatment. A sandwich TiO₂ square board with an area of 350 μm × 350 μm was defined by both wet etching and dry etching processes and the wet one was applied in the final process due to its advantages of easy control for the final structure. A pair of 150 nm Pt micro interdigitated electrodes with 50 nm Ti buffer layer was fabricated on the board by a lift-off process. The sensor chip was tested in a furnace with changing the O₂ concentration from 1.0% to 20% by monitoring its electrical resistance. Results showed that after several testing cycles the sensor’s output becomes stable, and its sensitivity is 0.054 with deviation 2.65 × 10⁻⁴ and hysteresis is 8.5%. Due to its simple fabrication process, the sensor has potential for application in environmental monitoring, where lower power consumption and small size are required. Full article

A Love Wave (LW) immunosensor was developed for the detection of carbaryl pesticide. The experimental setup consisted on: a compact electronic characterization circuit based on phase and amplitude detection at constant frequency; an automated flow injection system; a thermal control unit; a custom-made flow-through cell; and Quartz /SiO₂ LW sensors with a 40 μm wavelength and 120 MHz center frequency. The carbaryl detection was based on a competitive immunoassay format using LIB-CNH45 monoclonal antibody (MAb). Bovine Serum Albumin-CNH (BSA-CNH) carbaryl hapten-conjugate was covalently immobilized, via mercaptohexadecanoic acid self-assembled monolayer (SAM), onto the gold sensing area of the LW sensors. This immobilization allowed the reusability of the sensor for at least 70 assays without significant signal losses. The LW immunosensor showed a limit of detection (LOD) of 0.09 μg/L, a sensitivity of 0.31 μg/L and a linear working range of 0.14–1.63 μg/L. In comparison to other carbaryl immunosensors, the LW immunosensor achieved a high sensitivity and a low LOD. These features turn the LW immunosensor into a promising tool for applications that demand a high resolution, such as for the detection of pesticides in drinking water at European regulatory levels. Full article

Magnetic flux leakage (MFL) inspection is one of the most important and sensitive nondestructive testing approaches. For online MFL inspection of a long-range railway track or oil pipeline, a fast and effective defect profile estimating method based on a multi-power affine projection algorithm (MAPA) is proposed, where the depth of a sampling point is related with not only the MFL signals before it, but also the ones after it, and all of the sampling points related to one point appear as serials or multi-power. Defect profile estimation has two steps: regulating a weight vector in an MAPA filter and estimating a defect profile with the MAPA filter. Both simulation and experimental data are used to test the performance of the proposed method. The results demonstrate that the proposed method exhibits high speed while maintaining the estimated profiles clearly close to the desired ones in a noisy environment, thereby meeting the demand of accurate online inspection. Full article

With the development of 3D displays, user’s eye fatigue has been an important issue when viewing these displays. There have been previous studies conducted on eye fatigue related to 3D display use, however, most of these have employed a limited number of modalities for measurements, such as electroencephalograms (EEGs), biomedical signals, and eye responses. In this paper, we propose a new assessment of eye fatigue related to 3D display use based on multimodal measurements. compared to previous works Our research is novel in the following four ways: first, to enhance the accuracy of assessment of eye fatigue, we measure EEG signals, eye blinking rate (BR), facial temperature (FT), and a subjective evaluation (SE) score before and after a user watches a 3D display; second, in order to accurately measure BR in a manner that is convenient for the user, we implement a remote gaze-tracking system using a high speed (mega-pixel) camera that measures eye blinks of both eyes; thirdly, changes in the FT are measured using a remote thermal camera, which can enhance the measurement of eye fatigue, and fourth, we perform various statistical analyses to evaluate the correlation between the EEG signal, eye BR, FT, and the SE score based on the T-test, correlation matrix, and effect size. Results show that the correlation of the SE with other data (FT, BR, and EEG) is the highest, while those of the FT, BR, and EEG with other data are second, third, and fourth highest, respectively. Full article

In this paper, a remote lab for experimenting with a team of mobile robots is presented. Robots are built with the LEGO Mindstorms technology and user-defined control laws can be directly coded in the Matlab programming language and validated on the real system. The lab is versatile enough to be used for both teaching and research purposes. Students can easily go through a number of predefined mobile robotics experiences without having to worry about robot hardware or low-level programming languages. More advanced experiments can also be carried out by uploading custom controllers. The capability to have full control of the vehicles, together with the possibility to define arbitrarily complex environments through the definition of virtual obstacles, makes the proposed facility well suited to quickly test and compare different control laws in a real-world scenario. Moreover, the user can simulate the presence of different types of exteroceptive sensors on board of the robots or a specific communication architecture among the agents, so that decentralized control strategies and motion coordination algorithms can be easily implemented and tested. A number of possible applications and real experiments are presented in order to illustrate the main features of the proposed mobile robotics remote lab. Full article

In this paper, we present a framework for the hybrid omnidirectional and perspective robot vision system. Based on the hybrid imaging geometry, a generalized stereo approach is developed via the construction of virtual cameras. It is then used to rectify the hybrid image pair using the perspective projection model. The proposed method not only simplifies the computation of epipolar geometry for the hybrid imaging system, but also facilitates the stereo matching between the heterogeneous image formation. Experimental results for both the synthetic data and real scene images have demonstrated the feasibility of our approach. Full article

Robust dead reckoning is a complicated problem for wheeled mobile robots (WMRs), where the robots are faulty, such as the sticking of sensors or the slippage of wheels, for the discrete fault models and the continuous states have to be estimated simultaneously to reach a reliable fault diagnosis and accurate dead reckoning. Particle filters are one of the most promising approaches to handle hybrid system estimation problems, and they have also been widely used in many WMRs applications, such as pose tracking, SLAM, video tracking, fault identification, etc. In this paper, the readings of a laser range finder, which may be also interfered with by noises, are used to reach accurate dead reckoning. The main contribution is that a systematic method to implement fault diagnosis and dead reckoning in a particle filter framework concurrently is proposed. Firstly, the perception model of a laser range finder is given, where the raw scan may be faulty. Secondly, the kinematics of the normal model and different fault models for WMRs are given. Thirdly, the particle filter for fault diagnosis and dead reckoning is discussed. At last, experiments and analyses are reported to show the accuracy and efficiency of the presented method. Full article

Recent advances in the Micro Electro-Mechanical System (MEMS) technology have made wireless MEMS accelerometers an attractive tool for Structural Health Monitoring (SHM) of civil engineering structures. To date, sensors’ low sensitivity and accuracy—especially at very low frequencies—have imposed serious limitations for their application in monitoring large-sized structures. Conventionally, the MEMS sensor’s analog signals are converted to digital signals before radio-frequency (RF) wireless transmission. The conversion can cause a low sensitivity to the important low-frequency and low-amplitude signals. To overcome this difficulty, the authors have developed a MEMS accelerometer system, which converts the sensor output voltage to a frequency-modulated signal before RF transmission. This is achieved by using a Voltage to Frequency Conversion (V/F) instead of the conventional Analog to Digital Conversion (ADC). In this paper, a prototype MEMS accelerometer system is presented, which consists of a transmitter and receiver circuit boards. The former is equipped with a MEMS accelerometer, a V/F converter and a wireless RF transmitter, while the latter contains an RF receiver and a F/V converter for demodulating the signal. The efficacy of the MEMS accelerometer system in measuring low-frequency and low-amplitude dynamic responses is demonstrated through extensive laboratory tests and experiments on a flow-loop pipeline. Full article

The failure detector is one of the fundamental components that maintain high availability of Peer-to-Peer (P2P) networks. Under different network conditions, the adaptive failure detector based on quality of service (QoS) can achieve the detection time and accuracy required by upper applications with lower detection overhead. In P2P systems, complexity of network and high churn lead to high message loss rate. To reduce the impact on detection accuracy, baseline detection strategy based on retransmission mechanism has been employed widely in many P2P applications; however, Chen’s classic adaptive model cannot describe this kind of detection strategy. In order to provide an efficient service of failure detection in P2P systems, this paper establishes a novel QoS evaluation model for the baseline detection strategy. The relationship between the detection period and the QoS is discussed and on this basis, an adaptive failure detector (B-AFD) is proposed, which can meet the quantitative QoS metrics under changing network environment. Meanwhile, it is observed from the experimental analysis that B-AFD achieves better detection accuracy and time with lower detection overhead compared to the traditional baseline strategy and the adaptive detectors based on Chen’s model. Moreover, B-AFD has better adaptability to P2P network. Full article

In this paper, we propose an automatic and sequential method for the registration of an image sequence of a road area without ignoring scene-induced motion. This method contributes to a larger work, aiming at vehicle tracking. A typical image sequence is recorded from a helicopter hovering above the freeway. The demand for automation is inevitable due to the large number of images and continuous changes in the traffic situation and weather conditions. A framework is designed and implemented for this purpose. The registration errors are removed in a sequential way based on two homography assumptions. First, an approximate registration is obtained, which is efficiently refined in a second step, using a restricted search area. The results of the stabilization framework are demonstrated on an image sequence consisting of 1500 images and show that our method allows a registration between arbitrary images in the sequence with a geometric error of zero in pixel accuracy. Full article

This work reports the thermal modeling and characterization of a thyristor. The thyristor is used in a 6.5-MW generator excitation bridge. Temperature measurements are performed using fiber Bragg grating (FBG) sensors. These sensors have the benefits of being totally passive and immune to electromagnetic interference and also multiplexed in a single fiber. The thyristor thermal model consists of a second order equivalent electric circuit, and its power losses lead to an increase in temperature, while the losses are calculated on the basis of the excitation current in the generator. Six multiplexed FBGs are used to measure temperature and are embedded to avoid the effect of the strain sensitivity. The presented results show a relationship between field current and temperature oscillation and prove that this current can be used to determine the thermal model of a thyristor. The thermal model simulation presents an error of 1.5 °C, while the FBG used allows for the determination of the thermal behavior and the field current dependence. Since the temperature is a function of the field current, the corresponding simulation can be used to estimate the temperature in the thyristors. Full article

In this work, we have proposed a novel long-range surface plasmon resonance (LRSPR) sensor with sharp reflection spectrum, which consists of a glass prism, a (A/B)⁴-type waveguide-coupled layer and a metal layer. To reveal its sharp reflection spectrum perfectly, we have simulated the effects of all factors of this LRSPR sensor on the reflection spectrum, and finally presented the optimal parameters of the LRSPR sensor with sharp reflection spectrum. Full article

This paper proposes a novel motion field estimation method based on a 3D light detection and ranging (LiDAR) sensor for motion sensing for intelligent driverless vehicles and active collision avoidance systems. Unlike multiple target tracking methods, which estimate the motion state of detected targets, such as cars and pedestrians, motion field estimation regards the whole scene as a motion field in which each little element has its own motion state. Compared to multiple target tracking, segmentation errors and data association errors have much less significance in motion field estimation, making it more accurate and robust. This paper presents an intact 3D LiDAR-based motion field estimation method, including pre-processing, a theoretical framework for the motion field estimation problem and practical solutions. The 3D LiDAR measurements are first projected to small-scale polar grids, and then, after data association and Kalman filtering, the motion state of every moving grid is estimated. To reduce computing time, a fast data association algorithm is proposed. Furthermore, considering the spatial correlation of motion among neighboring grids, a novel spatial-smoothing algorithm is also presented to optimize the motion field. The experimental results using several data sets captured in different cities indicate that the proposed motion field estimation is able to run in real-time and performs robustly and effectively. Full article

In this paper, we present a novel texture image feature for Emotion Sensing in Speech (ESS). This idea is based on the fact that the texture images carry emotion-related information. The feature extraction is derived from time-frequency representation of spectrogram images. First, we transform the spectrogram as a recognizable image. Next, we use a cubic curve to enhance the image contrast. Then, the texture image information (TII) derived from the spectrogram image can be extracted by using Laws’ masks to characterize emotional state. In order to evaluate the effectiveness of the proposed emotion recognition in different languages, we use two open emotional databases including the Berlin Emotional Speech Database (EMO-DB) and eNTERFACE corpus and one self-recorded database (KHUSC-EmoDB), to evaluate the performance cross-corpora. The results of the proposed ESS system are presented using support vector machine (SVM) as a classifier. Experimental results show that the proposed TII-based feature extraction inspired by visual perception can provide significant classification for ESS systems. The two-dimensional (2-D) TII feature can provide the discrimination between different emotions in visual expressions except for the conveyance pitch and formant tracks. In addition, the de-noising in 2-D images can be more easily completed than de-noising in 1-D speech. Full article

This paper presents a new method for a composite dictionary matching pursuit algorithm, which is applied to vibration sensor signal feature extraction and fault diagnosis of a gearbox. Three advantages are highlighted in the new method. First, the composite dictionary in the algorithm has been changed from multi-atom matching to single-atom matching. Compared to non-composite dictionary single-atom matching, the original composite dictionary multi-atom matching pursuit (CD-MaMP) algorithm can achieve noise reduction in the reconstruction stage, but it cannot dramatically reduce the computational cost and improve the efficiency in the decomposition stage. Therefore, the optimized composite dictionary single-atom matching algorithm (CD-SaMP) is proposed. Second, the termination condition of iteration based on the attenuation coefficient is put forward to improve the sparsity and efficiency of the algorithm, which adjusts the parameters of the termination condition constantly in the process of decomposition to avoid noise. Third, composite dictionaries are enriched with the modulation dictionary, which is one of the important structural characteristics of gear fault signals. Meanwhile, the termination condition of iteration settings, sub-feature dictionary selections and operation efficiency between CD-MaMP and CD-SaMP are discussed, aiming at gear simulation vibration signals with noise. The simulation sensor-based vibration signal results show that the termination condition of iteration based on the attenuation coefficient enhances decomposition sparsity greatly and achieves a good effect of noise reduction. Furthermore, the modulation dictionary achieves a better matching effect compared to the Fourier dictionary, and CD-SaMP has a great advantage of sparsity and efficiency compared with the CD-MaMP. The sensor-based vibration signals measured from practical engineering gearbox analyses have further shown that the CD-SaMP decomposition and reconstruction algorithm is feasible and effective. Full article

Graphene has received significant attention due to its excellent properties currently. In this work, a nano-optomechanical system based on a doubly-clamped Z-shaped graphene nanoribbon (GNR) with an optical pump-probe scheme is proposed. We theoretically demonstrate the phenomenon of phonon-induced transparency and show an optical transistor in the system. In addition, the significantly enhanced nonlinear effect of the probe laser is also investigated, and we further put forward a nonlinear optical mass sensing that may be immune to detection noises. Molecules, such as NH₃ and NO₂, can be identified via using the nonlinear optical spectroscopy, which may be applied to environmental pollutant monitoring and trace chemical detection. Full article

The suspension system and socket fitting of artificial limbs have major roles and vital effects on the comfort, mobility, and satisfaction of amputees. This paper introduces a new pneumatic suspension system that overcomes the drawbacks of current suspension systems in donning and doffing, change in volume during daily activities, and pressure distribution in the socket-stump interface. An air pneumatic suspension system (APSS) for total-contact sockets was designed and developed. Pistoning and pressure distribution in the socket-stump interface were tested for the new APSS. More than 95% of the area between each prosthetic socket and liner was measured using a Tekscan F-Scan pressure measurement which has developed matrix-based pressure sensing systems. The variance in pressure around the stump was 8.76 kPa. APSS exhibits less pressure concentration around the stump, improved pressure distribution, easy donning and doffing, adjustability to remain fitted to the socket during daily activities, and more adaptability to the changes in stump volume. The volume changes were adjusted by utility of air pressure sensor. The vertical displacement point and reliability of suspension were assessed using a photographic method. The optimum pressure in every level of loading weight was 55 kPa, and the maximum displacement was 6 mm when 90 N of weight was loaded. Full article

We address the problem of data acquisition in large distributed wireless sensor networks (WSNs). We propose a method for data acquisition using the hierarchical routing method and compressive sensing for WSNs. Only a few samples are needed to recover the original signal with high probability since sparse representation technology is exploited to capture the similarities and differences of the original signal. To collect samples effectively in WSNs, a framework for the use of the hierarchical routing method and compressive sensing is proposed, using a randomized rotation of cluster-heads to evenly distribute the energy load among the sensors in the network. Furthermore, L1-minimization and Bayesian compressed sensing are used to approximate the recovery of the original signal from the smaller number of samples with a lower signal reconstruction error. We also give an extensive validation regarding coherence, compression rate, and lifetime, based on an analysis of the theory and experiments in the environment with real world signals. The results show that our solution is effective in a large distributed network, especially for energy constrained WSNs. Full article

A rapid, simple, and sensitive immunochromatographic test strip has been developed for testing residues of ciprofloxacin (CIP). A specific and sensitive monoclonal antibody (mAb) for CIP was generated by immunizing BALB/c mice with well-characterized CIP-Keyhole limpet haemocyanin. Under the optimized conditions, the cut-off limits of test strips for CIP were found to be 5 ng/mL in phosphate-buffered saline and 2.5 ng/mL in milk samples. Each test can be evaluated within 3 min. The cross-reactivities of the CIP test strip to enrofloxacin (ENR), norfloxacin (NOR), nadifloxacin (NDF), danofloxacin (DANO), pefloxacin (PEX), lomefloxacin (LOME), enoxacin (ENO), and sarafloxacin (SAR) were 71.4%, 71.4%, 66%, 50%, 33%, 20%, 12.5%, and 6.25%, respectively. The data indicate that the method is sensitive, specific, and has the advantages of simplicity and speed, therefore, this test strip is a useful screening method for the detection of CIP residues in milk samples. Full article

We design, fabricate and experimentally demonstrate a novel generic method to detect flow rates and precise changes of flow velocity in microfluidic devices. Using our method we can measure flow rates of ~2 mm/s with a resolution of 0.08 mm/s. The operation principle is based on the Doppler shifting of light diffracted from a self-generated periodic array of bubbles within the channel and using self-heterodyne detection to analyze the diffracted light. As such, the device is appealing for variety of “lab on chip” bio-applications where a simple and accurate speed measurement is needed, e.g., for flow-cytometry and cell sorting. Full article

An intrinsic Fabry-Perot interferometeric sensor based on a microfiber has been demonstrated. The micro-size suspended core is created by chemical etching a photonics crystal fiber, of which the cladding has a micrometer-spaced, hexagonal array of air holes. The sensing head is fabricated by chemical etching a short section of photonics crystal fiber spliced with a single mode fiber. The temperature sensing characteristic of the interferometer has also been demonstrated and a sensitivity 14.3 pm/°C is obtained. Full article

The unique properties of graphene, such as the high elasticity, mechanical strength, thermal conductivity, very high electrical conductivity and transparency, make them it an interesting material for stretchable electronic applications. In the work presented herein, the authors used graphene and carbon nanotubes to introduce chemical sensing properties into textile materials by means of a screen printing method. Carbon nanotubes and graphene pellets were dispersed in water and used as a printing paste in the screen printing process. Three printing paste compositions were prepared—0%, 1% and 3% graphene pellet content with a constant 3% carbon nanotube mass content. Commercially available materials were used in this process. As a substrate, a twill woven cotton fabric was utilized. It has been found that the addition of graphene to printing paste that contains carbon nanotubes significantly enhances the electrical conductivity and sensing properties of the final product. Full article

The catalytic behavior of zeolite catalysts for the ammonia-based selective catalytic reduction (SCR) of nitrogen oxides (NO_X) depends strongly on the type of zeolite material. An essential precondition for SCR is a previous ammonia gas adsorption that occurs on acidic sites of the zeolite. In order to understand and develop SCR active materials, it is crucial to know the amount of sorbed ammonia under reaction conditions. To support classical temperature-programmed desorption (TPD) experiments, a correlation of the dielectric properties with the catalytic properties and the ammonia sorption under reaction conditions appears promising. In this work, a laboratory test setup, which enables direct measurements of the dielectric properties of catalytic powder samples under a defined gas atmosphere and temperature by microwave cavity perturbation, has been developed. Based on previous investigations and computational simulations, a resonator cavity and a heating system were designed, installed and characterized. The resonator cavity is designed to operate in its TM₀₁₀ mode at 1.2 GHz. The first measurement of the ammonia loading of an H-ZSM-5 zeolite confirmed the operating performance of the test setup at constant temperatures of up to 300 °C. It showed how both real and imaginary parts of the relative complex permittivity are strongly correlated with the mass of stored ammonia. Full article

Bottom- and top-contact organic thin film transistors (OTFTs) were fabricated, using poly(3-hexylthiophene-2,5-diyl) (P3HT) and poly[2,5-bis(3-tetradecylthiophen-2-yl)thieno[3,2-b]thiophene] (PBTTT-C16) as p-type channel semiconductors. Four different types of OTFTs were fabricated and investigated as gas sensors against three volatile organic compounds, with different associated dipole moments. The OTFT-based sensor responses were evaluated with static and transient current measurements. A comparison between the different architectures and the relative organic semiconductor was made. Full article

The trajectory of the whole body center of mass (CoM) is useful as a reliable metric of postural stability. If the evaluation of a subject-specific CoM were available outside of the laboratory environment, it would improve the assessment of the effects of physical rehabilitation. This paper develops a method that enables tracking CoM position using low-cost sensors that can be moved around by a therapist or easily installed inside a patient’s home. Here, we compare the accuracy of a personalized CoM estimation using the statically equivalent serial chain (SESC) method and measurements obtained with the Kinect to the case of a SESC obtained with high-end equipment (Vicon). We also compare these estimates to literature-based ones for both sensors. The method was validated with seven able-bodied volunteers for whom the SESC was identified using 40 static postures. The literature-based estimation with Vicon measurements had a average error 24.9 ± 3.7 mm; this error was reduced to 12.8 ± 9.1 mm with the SESC identification. When using Kinect measurements, the literature-based estimate had an error of 118.4 ± 50.0 mm, while the SESC error was 26.6 ± 6.0 mm. The subject-specific SESC estimate using low-cost sensors has an equivalent performance as the literature-based one with high-end sensors. The SESC method can improve CoM estimation of elderly and neurologically impaired subjects by considering variations in their mass distribution. Full article

Mobile security is one of the most fundamental problems in Wireless Sensor Networks (WSNs). The data transmission path will be compromised for some disabled nodes. To construct a secure and reliable network, designing an adaptive route strategy which optimizes energy consumption and network lifetime of the aggregation cost is of great importance. In this paper, we address the reliable data aggregation route problem for WSNs. Firstly, to ensure nodes work properly, we propose a data aggregation route algorithm which improves the energy efficiency in the WSN. The construction process achieved through discrete particle swarm optimization (DPSO) saves node energy costs. Then, to balance the network load and establish a reliable network, an adaptive route algorithm with the minimal energy and the maximum lifetime is proposed. Since it is a non-linear constrained multi-objective optimization problem, in this paper we propose a DPSO with the multi-objective fitness function combined with the phenotype sharing function and penalty function to find available routes. Experimental results show that compared with other tree routing algorithms our algorithm can effectively reduce energy consumption and trade off energy consumption and network lifetime. Full article

An in-shoe pressure measurement (IPM) system can be used to measure center of pressure (COP) locations, and has fewer restrictions compared to the more conventional approach using a force platform. The insole of an IPM system, however, has its own coordinate system. To use an IPM system along with a motion capture system, there is thus a need to align the coordinate systems of the two measurement systems. To address this need, the current study examined two different approaches—rigid body transformation and nonlinear mapping (i.e., multilayer feed-forward neural network (MFNN))—to express COP measurements from an IPM system in the coordinate system of a motion capture system. Ten participants (five male and five female) completed several simulated manual material handling (MMH) activities, and during these activities the performance of the two approaches was assessed. Results indicated that: (1) performance varied between MMH activity types; and (2) a MFNN performed better than or comparable to the rigid body transformation, depending on the specific input variable sets used. Further, based on the results obtained, it was argued that a nonlinear mapping vs. rigid body transformation approach may be more effective to account for shoe deformation during MMH or potentially other types of physical activity. Full article

Gait identification is a valuable approach to identify humans at a distance. In thispaper, gait characteristics are analyzed based on an iPhone’s accelerometer and gyrometer,and a new approach is proposed for gait identification. Specifically, gait datasets are collectedby the triaxial accelerometer and gyrometer embedded in an iPhone. Then, the datasets areprocessed to extract gait characteristic parameters which include gait frequency, symmetrycoefficient, dynamic range and similarity coefficient of characteristic curves. Finally, aweighted voting scheme dependent upon the gait characteristic parameters is proposed forgait identification. Four experiments are implemented to validate the proposed scheme. Theattitude and acceleration solutions are verified by simulation. Then the gait characteristicsare analyzed by comparing two sets of actual data, and the performance of the weightedvoting identification scheme is verified by 40 datasets of 10 subjects. Full article

In this paper, an efficient direct data domain space-time adaptive processing (STAP) algorithm for moving targets detection is proposed, which is achieved based on the distinct spectrum features of clutter and target signals in the angle-Doppler domain. To reduce the computational complexity, the high-resolution angle-Doppler spectrum is obtained by finding the sparsest coefficients in the angle domain using the reduced-dimension data within each Doppler bin. Moreover, we will then present a knowledge-aided block-size detection algorithm that can discriminate between the moving targets and the clutter based on the extracted spectrum features. The feasibility and effectiveness of the proposed method are validated through both numerical simulations and raw data processing results. Full article

Navigation plays a vital role in our daily life. As traditional and commonly used navigation technologies, Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS) can provide accurate location information, but suffer from the accumulative error of inertial sensors and cannot be used in a satellite denied environment. The remarkable navigation ability of animals shows that the pattern of the polarization sky can be used for navigation. A bio-inspired POLarization Navigation Sensor (POLNS) is constructed to detect the polarization of skylight. Contrary to the previous approach, we utilize all the outputs of POLNS to compute input polarization angle, based on Least Squares, which provides optimal angle estimation. In addition, a new sensor calibration algorithm is presented, in which the installation angle errors and sensor biases are taken into consideration. Derivation and implementation of our calibration algorithm are discussed in detail. To evaluate the performance of our algorithms, simulation and real data test are done to compare our algorithms with several exiting algorithms. Comparison results indicate that our algorithms are superior to the others and are more feasible and effective in practice. Full article

The present research study deals with an electrically actuated MEMS device. An experimental investigation is performed, via frequency sweeps in a neighbourhood of the first natural frequency. Resonant behavior is explored, with special attention devoted to jump and pull-in dynamics. A theoretical single degree-of-freedom spring-mass model is derived. Classical numerical simulations are observed to properly predict the main nonlinear features. Nevertheless, some discrepancies arise, which are particularly visible in the resonant branch. They mainly concern the practical range of existence of each attractor and the final outcome after its disappearance. These differences are likely due to disturbances, which are unavoidable in practice, but have not been included in the model. To take disturbances into account, in addition to the classical local investigations, we consider the global dynamics and explore the robustness of the obtained results by performing a dynamical integrity analysis. Our aim is that of developing an applicable confident estimate of the system response. Integrity profiles and integrity charts are built to detect the parameter range where reliability is practically strong and where it becomes weak. Integrity curves exactly follow the experimental data. They inform about the practical range of actuality. We discuss the combined use of integrity charts in the engineering design. Although we refer to a particular case-study, the approach is very general. Full article

Wireless capsule endoscopy (WCE) has great advantages over traditional endoscopy because it is portable and easy to use, especially in remote monitoring health-services. However, during the WCE process, the large amount of captured video data demands a significant deal of computation to analyze and retrieve informative video frames. In order to facilitate efficient WCE data collection and browsing task, we present a resource- and bandwidth-aware WCE video summarization framework that extracts the representative keyframes of the WCE video contents by removing redundant and non-informative frames. For redundancy elimination, we use Jeffrey-divergence between color histograms and inter-frame Boolean series-based correlation of color channels. To remove non-informative frames, multi-fractal texture features are extracted to assist the classification using an ensemble-based classifier. Owing to the limited WCE resources, it is impossible for the WCE system to perform computationally intensive video summarization tasks. To resolve computational challenges, mobile-cloud architecture is incorporated, which provides resizable computing capacities by adaptively offloading video summarization tasks between the client and the cloud server. The qualitative and quantitative results are encouraging and show that the proposed framework saves information transmission cost and bandwidth, as well as the valuable time of data analysts in browsing remote sensing data. Full article

Ultrasonic is one of the most common uses of a non-destructive evaluation method for crack detection and characterization. The effectiveness of the acoustic-ultrasound Structural Health Monitoring (SHM) technique for the determination of the depth of the surface crack was presented. A method for ultrasonic sizing of surface cracks combined with the time domain and frequency spectrum was adopted. The ultrasonic frequency spectrum was obtained by Fourier transform technique. A series of test specimens with various depths of surface crack ranging from 1 mm to 8 mm was fabricated. The depth of the surface crack was evaluated using the pulse-echo technique. In this work, three different longitudinal waves with frequencies of 2.25 MHz, 5 MHz and 10 MHz were employed to investigate the effect of frequency on the sizing detection of surface cracks. Reasonable accuracies were achieved with measurement errors less than 7%. Full article

To correct an over-exposure within an image, the over-exposed region (OER) must first be detected. Detecting the OER accurately has a significant effect on the performance of the over-exposure correction. However, the results of conventional OER detection methods, which generally use the brightness and color information of each pixel, often deviate from the actual OER perceived by the human eye. To overcome this problem, in this paper, we propose a novel method for detecting the perceived OER more accurately. Based on the observation that recognizing the OER in an image is dependent on the saturation sensitivity of the human visual system (HVS), we detect the OER by thresholding the saturation value of each pixel. Here, a function of the proposed method, which is designed based on the results of a subjective evaluation on the saturation sensitivity of the HVS, adaptively determines the saturation threshold value using the color and the perceived brightness of each pixel. Experimental results demonstrate that the proposed method accurately detects the perceived OER, and furthermore, the over-exposure correction can be improved by adopting the proposed OER detection method. Full article

This study presents numerical simulations and experimental verification of a vibration-based damage detection technique. Health monitoring of a submerged pipe’s girth-weld against an advancing notch is attempted. Piezoelectric transducers are bonded on the pipe for sensing or actuation purposes. Vibration of the pipe is excited by two means: (i) an impulsive force; (ii) using one of the piezoelectric transducers as an actuator to propagate chirp waves into the pipe. The methodology adopts the empirical mode decomposition (EMD), which processes vibration data to establish energy-based damage indices. The results obtained from both the numerical and experimental studies confirm the integrity of the approach in identifying the existence, and progression of the advancing notch. The study also discusses and compares the performance of the two vibration excitation means in damage detection. Full article

A fully-integrated complementary metal-oxide semiconductor (CMOS) sensor for combined temperature and humidity measurements is presented. The main purpose of the device is to monitor the hermeticity of micro-packages for implanted integrated circuits and to ensure their safe operation by monitoring the operating temperature and humidity on-chip. The smart sensor has two modes of operation, in which either the temperature or humidity is converted into a digital code representing a frequency ratio between two oscillators. This ratio is determined by the ratios of the timing capacitances and bias currents in both oscillators. The reference oscillator is biased by a current whose temperature dependency is complementary to the proportional to absolute temperature (PTAT) current. For the temperature measurement, this results in an exceptional normalized sensitivity of about 0.77%/°C at the accepted expense of reduced linearity. The humidity sensor is a capacitor, whose value varies linearly with relative humidity (RH) with a normalized sensitivity of 0.055%/% RH. For comparison, two versions of the humidity sensor with an area of either 0.2 mm² or 1.2 mm² were fabricated in a commercial 0.18 μm CMOS process. The on-chip readout electronics operate from a 5 V power supply and consume a current of approximately 85 µA. Full article

Technological innovations in the field of disease prevention and maintenance of patient health have enabled the evolution of fields such as monitoring systems. One of the main advances is the development of real-time monitors that use intelligent and wireless communication technology. In this paper, a system is presented for the remote monitoring of the body temperature and heart rate of a patient by means of a wireless sensor network (WSN) and mobile augmented reality (MAR). The combination of a WSN and MAR provides a novel alternative to remotely measure body temperature and heart rate in real time during patient care. The system is composed of (1) hardware such as Arduino microcontrollers (in the patient nodes), personal computers (for the nurse server), smartphones (for the mobile nurse monitor and the virtual patient file) and sensors (to measure body temperature and heart rate), (2) a network layer using WiFly technology, and (3) software such as LabView, Android SDK, and DroidAR. The results obtained from tests show that the system can perform effectively within a range of 20 m and requires ten minutes to stabilize the temperature sensor to detect hyperthermia, hypothermia or normal body temperature conditions. Additionally, the heart rate sensor can detect conditions of tachycardia and bradycardia. Full article

Wearable technologies for health monitoring have become a reality in the last few years. So far, most research studies have focused on assessments of the technical performance of these systems, as well as the validation of the clinical outcomes. Nevertheless, the success in the acceptance of these solutions depends not only on the technical and clinical effectiveness, but on the final user acceptance. In this work the compliance of a telehealth system for the remote monitoring of Parkinson’s disease (PD) patients is presented with testing in 32 PD patients. This system, called PERFORM, is based on a Body Area Network (BAN) of sensors which has already been validated both from the technical and clinical point for view. Diverse methodologies (REBA, Borg and CRS scales in combination with a body map) are employed to study the comfort, biomechanical and physiological effects of the system. The test results allow us to conclude that the acceptance of this system is satisfactory with all the levels of effect on each component scoring in the lowest ranges. This study also provided useful insights and guidelines to lead to redesign of the system to improve patient compliance. Full article

In the practice of electrostatically actuated micro devices; the electrostatic force is implemented by sequentially actuated piecewise-electrodes which result in a traveling distributed electrostatic force. However; such force was modeled as a traveling concentrated electrostatic force in literatures. This article; for the first time; presents an analytical study on the stiffness variation of microstructures driven by a traveling piecewise electrode. The analytical model is based on the theory of shallow shell and uniform electrical field. The traveling electrode not only applies electrostatic force on the circular-ring but also alters its dynamical characteristics via the negative electrostatic stiffness. It is known that; when a structure is subjected to a traveling constant force; its natural mode will be resonated as the traveling speed approaches certain critical speeds; and each natural mode refers to exactly one critical speed. However; for the case of a traveling electrostatic force; the number of critical speeds is more than that of the natural modes. This is due to the fact that the traveling electrostatic force makes the resonant frequencies of the forward and backward traveling waves of the circular-ring different. Furthermore; the resonance and stability can be independently controlled by the length of the traveling electrode; though the driving voltage and traveling speed of the electrostatic force alter the dynamics and stabilities of microstructures. This paper extends the fundamental insights into the electromechanical behavior of microstructures driven by electrostatic forces as well as the future development of MEMS/NEMS devices with electrostatic actuation and sensing. Full article

Polymer composites with nanomaterials such as graphene nanoplatelets and carbon nanotubes are a new group of materials with high application possibilities in printed and flexible electronics. In this study such carbon nanomaterials were used as a conductive phase in polymer composites. Pastes with dispersed nanomaterials in PMMA and PVDF vehicles were screen printed on flexible substrates, and used as an active layer in pressure sensors, exploiting contact resistance phenomena. The relationship between resistance and pressure is nearly linear on a logarithmic scale for selected types of samples, and their response is several times higher than for similar sensors with graphite layers. The use of surfactants allowed us to fabricate evenly dispersed nanomaterials with different amount of nanoplatelets and nanotubes in the composites. The samples contained from 1.25 wt.% to 2 wt.% of graphene and 1 wt.% to 0.5 wt.% of nanotubes and exhibited diverse sheet resistivity. Experiments revealed the relationship between morphology and loading of functional phase in the polymer matrix and the sensors’ sensitivity. Full article

The deployment of the Ambient Intelligence (AmI) paradigm requires designing and integrating user-centered smart environments to assist people in their daily life activities. This research paper details an integration and validation of multiple heterogeneous sensors with hybrid reasoners that support decision making in order to monitor personal and environmental data at a smart home in a private way. The results innovate on knowledge-based platforms, distributed sensors, connected objects, accessibility and authentication methods to promote independent living for elderly people. TALISMAN+, the AmI framework deployed, integrates four subsystems in the smart home: (i) a mobile biomedical telemonitoring platform to provide elderly patients with continuous disease management; (ii) an integration middleware that allows context capture from heterogeneous sensors to program environment´s reaction; (iii) a vision system for intelligent monitoring of daily activities in the home; and (iv) an ontologies-based integrated reasoning platform to trigger local actions and manage private information in the smart home. The framework was integrated in two real running environments, the UPM Accessible Digital Home and MetalTIC house, and successfully validated by five experts in home care, elderly people and personal autonomy. Full article

In this paper, we address the task of gas distribution modeling in scenarios where multiple heterogeneous compounds are present. Gas distribution modeling is particularly useful in emission monitoring applications where spatial representations of the gaseous patches can be used to identify emission hot spots. In realistic environments, the presence of multiple chemicals is expected and therefore, gas discrimination has to be incorporated in the modeling process. The approach presented in this work addresses the task of gas distribution modeling by combining different non selective gas sensors. Gas discrimination is addressed with an open sampling system, composed by an array of metal oxide sensors and a probabilistic algorithm tailored to uncontrolled environments. For each of the identified compounds, the mapping algorithm generates a calibrated gas distribution model using the classification uncertainty and the concentration readings acquired with a photo ionization detector. The meta parameters of the proposed modeling algorithm are automatically learned from the data. The approach was validated with a gas sensitive robot patrolling outdoor and indoor scenarios, where two different chemicals were released simultaneously. The experimental results show that the generated multi compound maps can be used to accurately predict the location of emitting gas sources. Full article

In this study, a neural network-based square root of descending (SRD) order decomposition algorithm for compensating for nonlinear data generated by sensors is presented. The study aims at exploring the optimized decomposition of data 1.00,0.00,0.00 and minimizing the computational complexity and memory space of the training process. A linear decomposition algorithm, which automatically finds the optimal decomposition N and reduces the training time to $\frac{1}{\sqrt{N}}$and memory cost to $\frac{1}{N}$, has been implemented on nonlinear data obtained from an encoder. Particular focus is given to the theoretical access of estimating the numbers of hidden nodes and the precision of varying the decomposition method. Numerical experiments are designed to evaluate the effect of this algorithm. Moreover, a designed device for angular sensor calibration is presented. We conduct an experiment that samples the data of an encoder and compensates for the nonlinearity of the encoder to testify this novel algorithm. Full article

A new position estimation method by using the signals from two automatic identification system (AIS) stations is proposed in this paper. The time of arrival (TOA) method is enhanced with the displacement correction, so that the vessel’s position can be determined even for the situation where it can receive the signals from only two AIS base stations. Its implementation scheme based on the mathematical model is presented. Furthermore, performance analysis is carried out to illustrate the relation between the positioning errors and the displacement vector provided by auxiliary sensors. Finally, the positioning method is verified and its performance is evaluated by simulation. The results show that the positioning accuracy is acceptable. Full article

In the context of this work we evaluated a multisensory, noninvasive prototype platform for shake flask cultivations by monitoring three basic parameters (pH, pO₂ and biomass). The focus lies on the evaluation of the biomass sensor based on backward light scattering. The application spectrum was expanded to four new organisms in addition to E. coli K12 and S. cerevisiae [1]. It could be shown that the sensor is appropriate for a wide range of standard microorganisms, e.g., L. zeae, K. pastoris, A. niger and CHO-K1. The biomass sensor signal could successfully be correlated and calibrated with well-known measurement methods like OD_600, cell dry weight (CDW) and cell concentration. Logarithmic and Bleasdale-Nelder derived functions were adequate for data fitting. Measurements at low cell concentrations proved to be critical in terms of a high signal to noise ratio, but the integration of a custom made light shade in the shake flask improved these measurements significantly. This sensor based measurement method has a high potential to initiate a new generation of online bioprocess monitoring. Metabolic studies will particularly benefit from the multisensory data acquisition. The sensor is already used in labscale experiments for shake flask cultivations. Full article

The stochastic error characteristics of the Kinect sensing device are presented for each axis direction. Depth (z) directional error is measured using a flat surface, and horizontal (x) and vertical (y) errors are measured using a novel 3D checkerboard. Results show that the stochastic nature of the Kinect measurement error is affected mostly by the depth at which the object being sensed is located, though radial factors must be considered, as well. Measurement and statistics-based models are presented for the stochastic error in each axis direction, which are based on the location and depth value of empirical data measured for each pixel across the entire field of view. The resulting models are compared against existing Kinect error models, and through these comparisons, the proposed model is shown to be a more sophisticated and precise characterization of the Kinect error distributions. Full article

Disaster warning and surveillance systems have been widely applied to help the public be aware of an emergency. However, existing warning systems are unable to cooperate with household appliances or embedded controllers; that is, they cannot provide enough time for preparedness and evacuation, especially for disasters like earthquakes. In addition, the existing warning and surveillance systems are not responsible for collecting sufficient information inside a building for relief workers to conduct a proper rescue action after a disaster happens. In this paper, we describe the design and implementation of a proof of concept prototype, named the active disaster response system (ADRS), which automatically performs emergency tasks when an earthquake happens. ADRS can interpret Common Alerting Protocol (CAP) messages, published by an official agency, and actuate embedded controllers to perform emergency tasks to respond to the alerts. Examples of emergency tasks include opening doors and windows and cutting off power lines and gas valves. In addition, ADRS can maintain a temporary network by utilizing the embedded controllers; hence, victims trapped inside a building are still able to post emergency messages if the original network is disconnected. We conducted a field trial to evaluate the effectiveness of ADRS after an earthquake happened. Our results show that compared to manually operating emergency tasks, ADRS can reduce the operation time by up to 15 s, which is long enough for people to get under sturdy furniture, or to evacuate from the third floor to the first floor, or to run more than 100 m. Full article

The use of action cameras for photogrammetry purposes is not widespread due to the fact that until recently the images provided by the sensors, using either still or video capture mode, were not big enough to perform and provide the appropriate analysis with the necessary photogrammetric accuracy. However, several manufacturers have recently produced and released new lightweight devices which are: (a) easy to handle, (b) capable of performing under extreme conditions and more importantly (c) able to provide both still images and video sequences of high resolution. In order to be able to use the sensor of action cameras we must apply a careful and reliable self-calibration prior to the use of any photogrammetric procedure, a relatively difficult scenario because of the short focal length of the camera and its wide angle lens that is used to obtain the maximum possible resolution of images. Special software, using functions of the OpenCV library, has been created to perform both the calibration and the production of undistorted scenes for each one of the still and video image capturing mode of a novel action camera, the GoPro Hero 3 camera that can provide still images up to 12 Mp and video up 8 Mp resolution. Full article

Currently, driver drowsiness detectors using video based technology is being widely studied. Eyelid closure degree (ECD) is the main measure of the video-based methods, however, drawbacks such as brightness limitations and practical hurdles such as distraction of the drivers limits its success. This study presents a way to compute the ECD using EEG sensors instead of video-based methods. The premise is that the ECD exhibits a linear relationship with changes of the occipital EEG. A total of 30 subjects are included in this study: ten of them participated in a simple proof-of-concept experiment to verify the linear relationship between ECD and EEG, and then twenty participated in a monotonous highway driving experiment in a driving simulator environment to test the robustness of the linear relationship in real-life applications. Taking the video-based method as a reference, the Alpha power percentage from the O2 channel is found to be the best input feature for linear regression estimation of the ECD. The best overall squared correlation coefficient (SCC, denoted by r²) and mean squared error (MSE) validated by linear support vector regression model and leave one subject out method is r² = 0.930 and MSE = 0.013. The proposed linear EEG-ECD model can achieve 87.5% and 70.0% accuracy for male and female subjects, respectively, for a driver drowsiness application, percentage eyelid closure over the pupil over time (PERCLOS). This new ECD estimation method not only addresses the video-based method drawbacks, but also makes ECD estimation more computationally efficient and easier to implement in EEG sensors in a real time way. Full article

Research on real-time health systems have received great attention during recent years and the needs of high-quality personal multichannel medical signal compression for personal medical product applications are increasing. The international MPEG-4 audio lossless coding (ALS) standard supports a joint channel-coding scheme for improving compression performance of multichannel signals and it is very efficient compression method for multi-channel biosignals. However, the computational complexity of such a multichannel coding scheme is significantly greater than that of other lossless audio encoders. In this paper, we present a multichannel hardware encoder based on a low-complexity joint-coding technique and shared multiplier scheme for portable devices. A joint-coding decision method and a reference channel selection scheme are modified for a low-complexity joint coder. The proposed joint coding decision method determines the optimized joint-coding operation based on the relationship between the cross correlation of residual signals and the compression ratio. The reference channel selection is designed to select a channel for the entropy coding of the joint coding. The hardware encoder operates at a 40 MHz clock frequency and supports two-channel parallel encoding for the multichannel monitoring system. Experimental results show that the compression ratio increases by 0.06%, whereas the computational complexity decreases by 20.72% compared to the MPEG-4 ALS reference software encoder. In addition, the compression ratio increases by about 11.92%, compared to the single channel based bio-signal lossless data compressor. Full article

Precise point positioning (PPP) technology is mostly implemented with an ambiguity-float solution. Its performance may be further improved by performing ambiguity-fixed resolution. Currently, the PPP integer ambiguity resolutions (IARs) are mainly based on GPS-only measurements. The integration of GPS and GLONASS can speed up the convergence and increase the accuracy of float ambiguity estimates, which contributes to enhancing the success rate and reliability of fixing ambiguities. This paper presents an approach of combined GPS/GLONASS PPP with fixed GPS ambiguities (GGPPP-FGA) in which GPS ambiguities are fixed into integers, while all GLONASS ambiguities are kept as float values. An improved minimum constellation method (MCM) is proposed to enhance the efficiency of GPS ambiguity fixing. Datasets from 20 globally distributed stations on two consecutive days are employed to investigate the performance of the GGPPP-FGA, including the positioning accuracy, convergence time and the time to first fix (TTFF). All datasets are processed for a time span of three hours in three scenarios, i.e., the GPS ambiguity-float solution, the GPS ambiguity-fixed resolution and the GGPPP-FGA resolution. The results indicate that the performance of the GPS ambiguity-fixed resolutions is significantly better than that of the GPS ambiguity-float solutions. In addition, the GGPPP-FGA improves the positioning accuracy by 38%, 25% and 44% and reduces the convergence time by 36%, 36% and 29% in the east, north and up coordinate components over the GPS-only ambiguity-fixed resolutions, respectively. Moreover, the TTFF is reduced by 27% after adding GLONASS observations. Wilcoxon rank sum tests and chi-square two-sample tests are made to examine the significance of the improvement on the positioning accuracy, convergence time and TTFF. Full article

The autonomous vehicle is an automated system equipped with features like environment perception, decision-making, motion planning, and control and execution technology. Navigating in an unstructured and complex environment is a huge challenge for autonomous vehicles, due to the irregular shape of road, the requirement of real-time planning, and the nonholonomic constraints of vehicle. This paper presents a motion planning method, based on the Radial Basis Function (RBF) neural network, to guide the autonomous vehicle in unstructured environments. The proposed algorithm extracts the drivable region from the perception grid map based on the global path, which is available in the road network. The sample points are randomly selected in the drivable region, and a gradient descent method is used to train the RBF network. The parameters of the motion-planning algorithm are verified through the simulation and experiment. It is observed that the proposed approach produces a flexible, smooth, and safe path that can fit any road shape. The method is implemented on autonomous vehicle and verified against many outdoor scenes; furthermore, a comparison of proposed method with the existing well-known Rapidly-exploring Random Tree (RRT) method is presented. The experimental results show that the proposed method is highly effective in planning the vehicle path and offers better motion quality. Full article

Changing the position of the Center of Gravity (CoG) for an aerial vehicle is a challenging part in navigation, and control of such vehicles. In this paper, an all-accelerometers-based inertial measurement unit is presented, with a proposed method for on-line estimation of the position of the CoG. The accelerometers’ readings are used to find and correct the vehicle’s angular velocity and acceleration using an Extended Kalman Filter. Next, the accelerometers’ readings along with the estimated angular velocity and acceleration are used in an identification scheme to estimate the position of the CoG and the vehicle’s linear acceleration. The estimated position of the CoG and motion measurements can then be used to update the control rules to achieve better trim conditions for the air vehicle. Full article

The pulse oximeter is a popular instrument to monitor the arterial oxygen saturation (SPO₂). Although a fingertip-type pulse oximeter is the mainstream one on the market at present, it is still inconvenient for long-term monitoring, in particular, with respect to motion. Therefore, the development of a wearable pulse oximeter, such as a finger base-type pulse oximeter, can effectively solve the above issue. However, the tissue structure of the finger base is complex, and there is lack of detailed information on the effect of the light source and detector placement on measuring SPO₂. In this study, the practicability of a ring-type pulse oximeter with a multi-detector was investigated by optical human tissue simulation. The optimal design of a ring-type pulse oximeter that can provide the best efficiency of measuring SPO₂ was discussed. The efficiency of ring-type pulse oximeters with a single detector and a multi-detector was also discussed. Finally, a wearable and wireless ring-type pulse oximeter was also implemented to validate the simulation results and was compared with the commercial fingertip-type pulse oximeter. Full article

Although nonlinear H∞ (NH∞) filters offer good performance without requiring assumptions concerning the characteristics of process and/or measurement noises, they still require additional tuning parameters that remain fixed and that need to be determined through trial and error. To address issues associated with NH∞ filters, a new SINS/GPS sensor fusion scheme known as the Fuzzy Adaptive Nonlinear H∞ (FANH∞) filter is proposed for the Unmanned Aerial Vehicle (UAV) localization problem. Based on a real-time Fuzzy Inference System (FIS), the FANH∞ filter continually adjusts the higher order of the Taylor development thorough adaptive bounds and adaptive disturbance attenuation , which significantly increases the UAV localization performance. The results obtained using the FANH∞ navigation filter are compared to the NH∞ navigation filter results and are validated using a 3D UAV flight scenario. The comparison proves the efficiency and robustness of the UAV localization process using the FANH∞ filter. Full article

Operating system (OS) technology is significant for the proliferation of the wireless sensor network (WSN). With an outstanding OS; the constrained WSN resources (processor; memory and energy) can be utilized efficiently. Moreover; the user application development can be served soundly. In this article; a new hybrid; real-time; memory-efficient; energy-efficient; user-friendly and fault-tolerant WSN OS MIROS is designed and implemented. MIROS implements the hybrid scheduler and the dynamic memory allocator. Real-time scheduling can thus be achieved with low memory consumption. In addition; it implements a mid-layer software EMIDE (Efficient Mid-layer Software for User-Friendly Application Development Environment) to decouple the WSN application from the low-level system. The application programming process can consequently be simplified and the application reprogramming performance improved. Moreover; it combines both the software and the multi-core hardware techniques to conserve the energy resources; improve the node reliability; as well as achieve a new debugging method. To evaluate the performance of MIROS; it is compared with the other WSN OSes (TinyOS; Contiki; SOS; openWSN and mantisOS) from different OS concerns. The final evaluation results prove that MIROS is suitable to be used even on the tight resource-constrained WSN nodes. It can support the real-time WSN applications. Furthermore; it is energy efficient; user friendly and fault tolerant. Full article

The measurement of precise along-track displacements has been made with the multiple-aperture interferometry (MAI). The empirical accuracies of the MAI measurements are about 6.3 and 3.57 cm for ERS and ALOS data, respectively. However, the estimated empirical accuracies cannot be generalized to any interferometric pair because they largely depend on the processing parameters and coherence of the used SAR data. A theoretical formula is given to calculate an expected MAI measurement accuracy according to the system and processing parameters and interferometric coherence. In this paper, we have investigated the expected MAI measurement accuracy on the basis of the theoretical formula for the existing X-, C- and L-band satellite SAR systems. The similarity between the expected and empirical MAI measurement accuracies has been tested as well. The expected accuracies of about 2–3 cm and 3–4 cm (γ = 0.8) are calculated for the X- and L-band SAR systems, respectively. For the C-band systems, the expected accuracy of Radarsat-2 ultra-fine is about 3–4 cm and that of Sentinel-1 IW is about 27 cm (γ = 0.8). The results indicate that the expected MAI measurement accuracy of a given interferometric pair can be easily calculated by using the theoretical formula. Full article

Knowledge of crop abiotic and biotic stress is important for optimal irrigation management. While spectral reflectance and infrared thermometry provide a means to quantify crop stress remotely, these measurements can be cumbersome. Computer vision offers an inexpensive way to remotely detect crop stress independent of vegetation cover. This paper presents a technique using computer vision to detect disease stress in wheat. Digital images of differentially stressed wheat were segmented into soil and vegetation pixels using expectation maximization (EM). In the first season, the algorithm to segment vegetation from soil and distinguish between healthy and stressed wheat was developed and tested using digital images taken in the field and later processed on a desktop computer. In the second season, a wireless camera with near real-time computer vision capabilities was tested in conjunction with the conventional camera and desktop computer. For wheat irrigated at different levels and inoculated with wheat streak mosaic virus (WSMV), vegetation hue determined by the EM algorithm showed significant effects from irrigation level and infection. Unstressed wheat had a higher hue (118.32) than stressed wheat (111.34). In the second season, the hue and cover measured by the wireless computer vision sensor showed significant effects from infection (p = 0.0014), as did the conventional camera (p < 0.0001). Vegetation hue obtained through a wireless computer vision system in this study is a viable option for determining biotic crop stress in irrigation scheduling. Such a low-cost system could be suitable for use in the field in automated irrigation scheduling applications. Full article

This paper describes a new method based on a voltammetric electronic tongue (ET) for the recognition of distinctive features in coffee samples. An ET was directly applied to different samples from the main Mexican coffee regions without any pretreatment before the analysis. The resulting electrochemical information was modeled with two different mathematical tools, namely Linear Discriminant Analysis (LDA) and Support Vector Machines (SVM). Growing conditions (i.e., organic or non-organic practices and altitude of crops) were considered for a first classification. LDA results showed an average discrimination rate of 88% ± 6.53% while SVM successfully accomplished an overall accuracy of 96.4% ± 3.50% for the same task. A second classification based on geographical origin of samples was carried out. Results showed an overall accuracy of 87.5% ± 7.79% for LDA and a superior performance of 97.5% ± 3.22% for SVM. Given the complexity of coffee samples, the high accuracy percentages achieved by ET coupled with SVM in both classification problems suggested a potential applicability of ET in the assessment of selected coffee features with a simpler and faster methodology along with a null sample pretreatment. In addition, the proposed method can be applied to authentication assessment while improving cost, time and accuracy of the general procedure. Full article

In this paper, an artificial olfactory system (Electronic Nose) that mimics thebiological olfactory system is introduced. The device consists of a Large-Scale ChemicalSensor Array (16; 384 sensors, made of 24 different kinds of conducting polymer materials)that supplies data to software modules, which perform advanced data processing. Inparticular, the paper concentrates on the software components consisting, at first, of acrucial step that normalizes the heterogeneous sensor data and reduces their inherent noise.Cleaned data are then supplied as input to a data reduction procedure that extracts the mostinformative and discriminant directions in order to get an efficient representation in a lowerdimensional space where it is possible to more easily find a robust mapping between theobserved outputs and the characteristics of the odors in input to the device. Experimentalqualitative proofs of the validity of the procedure are given by analyzing data acquired fortwo different pure analytes and their binary mixtures. Moreover, a classification task isperformed in order to explore the possibility of automatically recognizing pure compoundsand to predict binary mixture concentrations. Full article

The mechanical scanning of a single element transducer has been mostly utilized for high-frequency ultrasound imaging. However, it requires space for the mechanical motion of the transducer. In this paper, a rotational scanning ultrasound biomicroscopy (UBM) system equipped with a high-frequency angled needle transducer is designed and implemented in order to minimize the space required. It was applied to ex vivo ultrasound imaging of porcine posterior ocular tissues through a minimal incision hole of 1 mm in diameter. The retina and sclera for the one eye were visualized in the relative rotating angle range of 270° ~ 330° and at a distance range of 6 ~ 7 mm, whereas the tissues of the other eye were observed in relative angle range of 160° ~ 220° and at a distance range of 7.5 ~ 9 mm. The layer between retina and sclera seemed to be bent because the distance between the transducer tip and the layer was varied while the transducer was rotated. Certin features of the rotation system such as the optimal scanning angle, step angle and data length need to be improved for ensure higher accuracy and precision. Moreover, the focal length should be considered for the image quality. This implementation represents the first report of a rotational scanning UBM system. Full article

In this work we demonstrate efficient quality control of a variety of gasoline and ethanol (gasohol) blends using a multimode interference (MMI) fiber sensor. The operational principle relies on the fact that the addition of ethanol to the gasohol blend reduces the refractive index (RI) of the gasoline. Since MMI sensors are capable of detecting small RI changes, the ethanol content of the gasohol blend is easily determined by tracking the MMI peak wavelength response. Gasohol blends with ethanol contents ranging from 0% to 50% has been clearly identified using this device, which provides a linear response with a maximum sensitivity of 0.270 nm/% EtOH. The sensor can also distinguish when water incorporated in the blend has exceeded the maximum volume tolerated by the gasohol blend, which is responsible for phase separation of the ethanol and gasoline and could cause serious engine failures. Since the MMI sensor is straightforward to fabricate and does not require any special coating it is a cost effective solution for real time and in-situ monitoring of the quality of gasohol blends. Full article

This study proposes a drowsiness detection approach based on the combination of several different detection methods, with robustness to the input signal loss. Hence, if one of the methods fails for any reason, the whole system continues to work properly. To choose correct combination of the available methods and to utilize the benefits of methods of different categories, an image processing-based technique as well as a method based on driver-vehicle interaction is used. In order to avoid driving distraction, any use of an intrusive method is prevented. A driving simulator is used to gather real data and then artificial neural networks are used in the structure of the designed system. Several tests were conducted on twelve volunteers while their sleeping situations during one day prior to the tests, were fully under control. Although the impact of the proposed system on the improvement of the detection accuracy is not remarkable, the results indicate the main advantages of the system are the reliability of the detections and robustness to the loss of the input signals. The high reliability of the drowsiness detection systems plays an important role to reduce drowsiness related road accidents and their associated costs. Full article

Skeletal muscle is the largest tissue structure in our body and plays an essential role for producing motion through integrated action with bones, tendons, ligaments and joints, for stabilizing body position, for generation of heat through cell respiration and for blood glucose disposal. A key function of skeletal muscle is force generation. Non-invasive and selective measurement of muscle contraction force in the field and in clinical settings has always been challenging. The aim of our work has been to develop a sensor that can overcome these difficulties and therefore enable measurement of muscle force during different contraction conditions. In this study, we tested the mechanical properties of a “Muscle Contraction” (MC) sensor during isometric muscle contraction in different length/tension conditions. The MC sensor is attached so that it indents the skin overlying a muscle group and detects varying degrees of tension during muscular contraction. We compared MC sensor readings over the biceps brachii (BB) muscle to dynamometric measurements of force of elbow flexion, together with recordings of surface EMG signal of BB during isometric contractions at 15° and 90° of elbow flexion. Statistical correlation between MC signal and force was very high at 15° (r = 0.976) and 90° (r = 0.966) across the complete time domain. Normalized SD or σ_N = σ/max(F_MC) was used as a measure of linearity of MC signal and elbow flexion force in dynamic conditions. The average was 8.24% for an elbow angle of 90° and 10.01% for an elbow of angle 15°, which indicates high linearity and good dynamic properties of MC sensor signal when compared to elbow flexion force. The next step of testing MC sensor potential will be to measure tension of muscle-tendon complex in conditions when length and tension change simultaneously during human motion. Full article

Surface plasmon resonance (SPR) is a novel optical sensing technique with a unique ability to monitor molecular binding in real-time for biological and chemical sensor applications. Interferometry is an excellent tool for accurate measurement of SPR changes, the measurement and comparison is made for the sensitivity, dynamic range and resolution of the different analytes using interferometry techniques. SPR interferometry can also employ phase detection in addition to the amplitude of the reflected light wave, and the phase changes more rapidly compared with other approaches, i.e., intensity, angle and wavelength. Therefore, the SPR phase interferometer offers the advantages of spatial phase resolution and high sensitivity. This work discusses the advancements in interferometric SPR methods to measure the phase shifts due to refractive index changes. The main application areas of SPR sensors are demonstrated, i.e., the Fabry-Perot interferometer, Michelson interferometer and Mach-Zehnder interferometer, with different configurations. The three interferometers are discussed in detail, and solutions are suggested to enhance the performance parameters that will aid in future biological and chemical sensors. Full article

Advancements in optical nanosensor development have enabled the design of sensors using synthetic molecular recognition elements through a recently developed method called Corona Phase Molecular Recognition (CoPhMoRe). The synthetic sensors resulting from these design principles are highly selective for specific analytes, and demonstrate remarkable stability for use under a variety of conditions. An essential element of nanosensor development hinges on the ability to understand the interface between nanoparticles and the associated corona phase surrounding the nanosensor, an environment outside of the range of traditional characterization tools, such as NMR. This review discusses the need for new strategies and instrumentation to study the nanoparticle corona, operating in both in vitro and in vivo environments. Approaches to instrumentation must have the capacity to concurrently monitor nanosensor operation and the molecular changes in the corona phase. A detailed overview of new tools for the understanding of CoPhMoRe mechanisms is provided for future applications. Full article

The humidity sensing characteristics of different sensing materials are important properties in order to monitor different products or events in a wide range of industrial sectors, research and development laboratories as well as daily life. The primary aim of this study is to compare the sensing characteristics, including impedance or resistance, capacitance, hysteresis, recovery and response times, and stability with respect to relative humidity, frequency, and temperature, of different materials. Various materials, including ceramics, semiconductors, and polymers, used for sensing relative humidity have been reviewed. Correlations of the different electrical characteristics of different doped sensor materials as the most unique feature of a material have been noted. The electrical properties of different sensor materials are found to change significantly with the morphological changes, doping concentration of different materials and film thickness of the substrate. Various applications and scopes are pointed out in the review article. We extensively reviewed almost all main kinds of relative humidity sensors and how their electrical characteristics vary with different doping concentrations, film thickness and basic sensing materials. Based on statistical tests, the zinc oxide-based sensing material is best for humidity sensor design since it shows extremely low hysteresis loss, minimum response and recovery times and excellent stability. Full article