Sensors, Volume 17, Issue 11 (November 2017) – 262 articles

Manual measurements of foot anthropometry can lead to errors since this task involves the experience of the specialist who performs them, resulting in different subjective measures from the same footprint. Moreover, some of the diagnoses that are given to classify a footprint deformity are based on a qualitative interpretation by the physician; there is no quantitative interpretation of the footprint. The importance of providing a correct and accurate diagnosis lies in the need to ensure that an appropriate treatment is provided for the improvement of the patient without risking his or her health. Therefore, this article presents a smart sensor that integrates the capture of the footprint, a low computational-cost analysis of the image and the interpretation of the results through a quantitative evaluation. The smart sensor implemented required the use of a camera (Logitech C920) connected to a Raspberry Pi 3, where a graphical interface was made for the capture and processing of the image, and it was adapted to a podoscope conventionally used by specialists such as orthopedist, physiotherapists and podiatrists. The footprint diagnosis smart sensor (FPDSS) has proven to be robust to different types of deformity, precise, sensitive and correlated in 0.99 with the measurements from the digitalized image of the ink mat. Full article

For many pedestrian detectors, background vs. foreground errors heavily influence the detection quality. Our main contribution is to design semantic regions of interest that extract the foreground target roughly to reduce the background vs. foreground errors of detectors. First, we generate a pedestrian heat map from the input image with a full convolutional neural network trained on the Caltech Pedestrian Dataset. Next, semantic regions of interest are extracted from the heat map by morphological image processing. Finally, the semantic regions of interest divide the whole image into foreground and background to assist the decision-making of detectors. We test our approach on the Caltech Pedestrian Detection Benchmark. With the help of our semantic regions of interest, the effects of the detectors have varying degrees of improvement. The best one exceeds the state-of-the-art. Full article

Climbing and descending stairs are demanding daily activities, and the monitoring of them may reveal the presence of musculoskeletal diseases at an early stage. A markerless system is needed to monitor such stair walking activity without mentally or physically disturbing the subject. Microsoft Kinect v2 has been used for gait monitoring, as it provides a markerless skeleton tracking function. However, few studies have used this device for stair walking monitoring, and the accuracy of its skeleton tracking function during stair walking has not been evaluated. Moreover, skeleton tracking is not likely to be suitable for estimating body joints during stair walking, as the form of the body is different from what it is when it walks on level surfaces. In this study, a new method of estimating the 3D position of the knee joint was devised that uses the depth data of Kinect v2. The accuracy of this method was compared with that of the skeleton tracking function of Kinect v2 by simultaneously measuring subjects with a 3D motion capture system. The depth data method was found to be more accurate than skeleton tracking. The mean error of the 3D Euclidian distance of the depth data method was 43.2 ± 27.5 mm, while that of the skeleton tracking was 50.4 ± 23.9 mm. This method indicates the possibility of stair walking monitoring for the early discovery of musculoskeletal diseases. Full article

This paper presents a price-searching model in which a source node (Alice) seeks friendly jammers that prevent eavesdroppers (Eves) from snooping legitimate communications by generating interference or noise. Unlike existing models, the distributed jammers also have data to send to their respective destinations and are allowed to access Alice’s channel if it can transmit sufficient jamming power, which is referred to as collaborative jamming in this paper. For the power used to deliver its own signal, the jammer should pay Alice. The price of the jammers’ signal power is set by Alice and provides a tradeoff between the signal and the jamming power. This paper presents, in closed-form, an optimal price that maximizes Alice’s benefit and the corresponding optimal power allocation from a jammers’ perspective by assuming that the network-wide channel knowledge is shared by Alice and jammers. For a multiple-jammer scenario where Alice hardly has the channel knowledge, this paper provides a distributed and interactive price-searching procedure that geometrically converges to an optimal price and shows that Alice by a greedy selection policy achieves certain diversity gain, which increases log-linearly as the number of (potential) jammers grows. Various numerical examples are presented to illustrate the behavior of the proposed model. Full article

This paper presents an extrinsic Fabry–Perot interferometer-based optical fiber sensor (EFPI) for measuring three-dimensional (3D) displacements, including interfacial sliding and debonding during delamination. The idea employs three spatially arranged EFPIs as the sensing elements. In our sensor, the three EFPIs are formed by three endfaces of three optical fibers and their corresponding inclined mirrors. Two coincident roof-like metallic structures are used to support the three fibers and the three mirrors, respectively. Our sensor was calibrated and then used to monitor interfacial sliding and debonding between a long square brick of mortar and its support structure (i.e., a steel base plate) during the drying/curing process. This robust and easy-to-manufacture triaxial EFPI-based 3D displacement sensor has great potential in structural health monitoring, the construction industry, oil well monitoring, and geotechnology. Full article

In this paper, we present a novel method for 3D pedestrian navigation of foot-mounted inertial systems by integrating a MEMS-IMU, barometer, and permanent magnet. Zero-velocity update (ZUPT) is a well-known algorithm to eliminate the accumulated error of foot-mounted inertial systems. However, the ZUPT stance phase detector using acceleration and angular rate is threshold-based, which may cause incorrect stance phase estimation in the running gait pattern. A permanent magnet-based ZUPT detector is introduced to solve this problem. Peaks extracted from the magnetic field strength waveform are mid-stances of stance phases. A model of peak-peak information and stance phase duration is developed to have a quantitative calculation method of stance phase duration in different movement patterns. Height estimation using barometer is susceptible to the environment. A height difference information aided barometer (HDIB) algorithm integrating MEMS-IMU and barometer is raised to have a better height estimation. The first stage of HDIB is to distinguish level ground/upstairs/downstairs and the second stage is to calculate height using reference atmospheric pressure obtained from the first stage. At last, a ZUPT-based adaptive average window length algorithm (ZUPT-AAWL) is proposed to calculate the true total travelled distance to have a more accurate percentage error (TTDE). This proposed method is verified via multiple experiments. Numerical results show that TTDE ranges from 0.32% to 1.04% in both walking and running gait patterns, and the height estimation error is from 0 m to 2.35 m. Full article

Machine-to-machine (M2M) communication is a key enabling technology for industrial internet of things (IIoT)-empowered industrial networks, where machines communicate with one another for collaborative automation and intelligent optimisation. This new industrial computing paradigm features high-quality connectivity, ubiquitous messaging, and interoperable interactions between machines. However, manufacturing IIoT applications have specificities that distinguish them from many other internet of things (IoT) scenarios in machine communications. By highlighting the key requirements and the major technical gaps of M2M in industrial applications, this article describes a collaboration-oriented M2M (CoM2M) messaging mechanism focusing on flexible connectivity and discovery, ubiquitous messaging, and semantic interoperability that are well suited for the production line-scale interoperability of manufacturing applications. The designs toward machine collaboration and data interoperability at both the communication and semantic level are presented. Then, the application scenarios of the presented methods are illustrated with a proof-of-concept implementation in the PicknPack food packaging line. Eventually, the advantages and some potential issues are discussed based on the PicknPack practice. Full article

Near-infrared (NIR) spectroscopy was applied for the determination of total soluble solid contents (SSC) of single Ruby Seedless grape berries using both benchtop Fourier transform (VECTOR 22/N) and portable grating scanning (SupNIR-1500) spectrometers in this study. The results showed that the best SSC prediction was obtained by VECTOR 22/N in the range of 12,000 to 4000 cm⁻¹ (833–2500 nm) for Ruby Seedless with determination coefficient of prediction (R_p²) of 0.918, root mean squares error of prediction (RMSEP) of 0.758% based on least squares support vector machine (LS-SVM). Calibration transfer was conducted on the same spectral range of two instruments (1000–1800 nm) based on the LS-SVM model. By conducting Kennard-Stone (KS) to divide sample sets, selecting the optimal number of standardization samples and applying Passing-Bablok regression to choose the optimal instrument as the master instrument, a modified calibration transfer method between two spectrometers was developed. When 45 samples were selected for the standardization set, the linear interpolation-piecewise direct standardization (linear interpolation-PDS) performed well for calibration transfer with R_p² of 0.857 and RMSEP of 1.099% in the spectral region of 1000–1800 nm. And it was proved that re-calculating the standardization samples into master model could improve the performance of calibration transfer in this study. This work indicated that NIR could be used as a rapid and non-destructive method for SSC prediction, and provided a feasibility to solve the transfer difficulty between totally different NIR spectrometers. Full article

Although at present legislation does not allow drivers in a Level 3 autonomous vehicle to engage in a secondary task, there may become a time when it does. Monitoring the behaviour of drivers engaging in various non-driving activities (NDAs) is crucial to decide how well the driver will be able to take over control of the vehicle. One limitation of the commonly used face-based head tracking system, using cameras, is that sufficient features of the face must be visible, which limits the detectable angle of head movement and thereby measurable NDAs, unless multiple cameras are used. This paper proposes a novel orientation sensor based head tracking system that includes twin devices, one of which measures the movement of the vehicle while the other measures the absolute movement of the head. Measurement error in the shaking and nodding axes were less than 0.4°, while error in the rolling axis was less than 2°. Comparison with a camera-based system, through in-house tests and on-road tests, showed that the main advantage of the proposed system is the ability to detect angles larger than 20° in the shaking and nodding axes. Finally, a case study demonstrated that the measurement of the shaking and nodding angles, produced from the proposed system, can effectively characterise the drivers’ behaviour while engaged in the NDAs of chatting to a passenger and playing on a smartphone. Full article

Blood has been the most reliable body fluid commonly used for the diagnosis of diseases. Although there have been promising investigations for the development of novel lab-on-a-chip devices to utilize other body fluids such as urine and sweat samples in diagnosis, their stability remains a problem that limits the reliability and accuracy of readouts. Hence, accurate and quantitative separation and characterization of blood cells are still crucial. The first step in achieving high-resolution characteristics for specific cell subpopulations from the whole blood is the isolation of pure cell populations from a mixture of cell suspensions. Second, live cells need to be purified from dead cells; otherwise, dead cells might introduce biases in the measurements. In addition, the separation and characterization methods being used must preserve the genetic and phenotypic properties of the cells. Among the characterization and separation approaches, dielectrophoresis (DEP) is one of the oldest and most efficient label-free quantification methods, which directly purifies and characterizes cells using their intrinsic, physical properties. In this study, we present the dielectrophoretic separation and characterization of live and dead monocytes using 3D carbon-electrodes. Our approach successfully removed the dead monocytes while preserving the viability of the live monocytes. Therefore, when blood analyses and disease diagnosis are performed with enriched, live monocyte populations, this approach will reduce the dead-cell contamination risk and achieve more reliable and accurate test results. Full article

Surface water used for drinking water production is frequently monitored in The Netherlands using whole organism biomonitors, with for example Daphnia magna or Dreissena mussels, which respond to changes in the water quality. However, not all human-relevant toxic compounds can be detected by these biomonitors. Therefore, a new on-line biosensor has been developed, containing immobilized genetically modified bacteria, which respond to genotoxicity in the water by emitting luminescence. The performance of this sensor was tested under laboratory conditions, as well as under field conditions at a monitoring station along the river Meuse in The Netherlands. The sensor was robust and easy to clean, with inert materials, temperature control and nutrient feed for the reporter organisms. The bacteria were immobilized in sol-gel on either an optical fiber or a glass slide and then continuously exposed to water. Since the glass slide was more sensitive and robust, only this setup was used in the field. The sensor responded to spikes of genotoxic compounds in the water with a minimal detectable concentration of 0.01 mg/L mitomycin C in the laboratory and 0.1 mg/L mitomycin C in the field. With further optimization, which should include a reduction in daily maintenance, the sensor has the potential to become a useful addition to the currently available biomonitors. Full article

This work addresses the problem of tracking a signal-emitting mobile target in wireless sensor networks (WSNs) with navigated mobile sensors. The sensors are properly equipped to acquire received signal strength (RSS) and angle of arrival (AoA) measurements from the received signal, while the target transmit power is assumed not known. We start by showing how to linearize the highly non-linear measurement model. Then, by employing a Bayesian approach, we combine the linearized observation model with prior knowledge extracted from the state transition model. Based on the maximum a posteriori (MAP) principle and the Kalman filtering (KF) framework, we propose new MAP and KF algorithms, respectively. We also propose a simple and efficient mobile sensor navigation procedure, which allows us to further enhance the estimation accuracy of our algorithms with a reduced number of sensors. Model flaws, which result in imperfect knowledge about the path loss exponent (PLE) and the true mobile sensors’ locations, are taken into consideration. We have carried out an extensive simulation study, and our results confirm the superiority of the proposed algorithms, as well as the effectiveness of the proposed navigation routine. Full article

Surface-enhanced Raman spectroscopy (SERS) is a powerful technique for the discrimination, identification, and potential quantification of certain compounds/organisms. However, its real application is challenging due to the multiple interference from the complicated detection matrix. Therefore, selective/specific detection is crucial for the real application of SERS technique. We summarize in this review five selective/specific detection techniques (chemical reaction, antibody, aptamer, molecularly imprinted polymers and microfluidics), which can be applied for the rapid and reliable selective/specific detection when coupled with SERS technique. Full article

Human Activity Recognition (HAR) is one of the main subjects of study in the areas of computer vision and machine learning due to the great benefits that can be achieved. Examples of the study areas are: health prevention, security and surveillance, automotive research, and many others. The proposed approaches are carried out using machine learning techniques and present good results. However, it is difficult to observe how the descriptors of human activities are grouped. In order to obtain a better understanding of the the behavior of descriptors, it is important to improve the abilities to recognize the human activities. This paper proposes a novel approach for the HAR based on acoustic data and similarity networks. In this approach, we were able to characterize the sound of the activities and identify those activities looking for similarity in the sound pattern. We evaluated the similarity of the sounds considering mainly two features: the sound location and the materials that were used. As a result, the materials are a good reference classifying the human activities compared with the location. Full article

The security and privacy provided by Visible Light Communication (VLC) technologies is an area that has been slightly addressed due to the misconception that, since light does not go through solid objects like walls, VLC-based communications cannot be eavesdropped on by outside observers. As an upcoming technology, VLC is expected to be used in multiple environments were, due to radio frequency RF overuse or limitations, RF solutions cannot or should not be employed. In this work, we study the eavesdropping characteristics of a VLC-based communication. To evaluate these concerns, a two-step process was followed. First, several simulations of a standardly used scenario were run. Later on, experimental tests were performed. Following those tests, the results of the simulations and the experimental tests were analyzed. The results of these simulations and tests seemed to indicate that VLC channels can be eavesdropped on without considerable difficulties. Furthermore, the results showed that sniffing attacks could be performed from areas outside the expected coverage of the VLC infrastructure. Finally, the use of the simulation such as the one implemented in this work to recognize places from which sniffing is possible helps determine the risk for eavesdropping that our VLC-based network has. Full article

A new stiffness measurement method is proposed that utilizes the lateral deformation profile of an object under indentation. The system consists of a force measurement module between a pair of equidistant touch sensing modules. Unique feature of the method is that by adjusting the touch module separation, indenter protrusion, and spring constant of the force sensing module, one can choose a desired sensing range for the force module. This feature helps to enhance the stiffness differentiation between objects of similar hardness and avoids measurement saturation. We devised a portable measurement system based on the method, and tested its performance with several materials including polymer foams and human skin. Full article

This paper developed and evaluated a quantitative image analysis method to measure the concentration of the nanoparticles on which alkaline phosphatase (AP) was immobilized. These AP-labeled nanoparticles are widely used as signal markers for tagging biomolecules at nanometer and sub-nanometer scales. The AP-labeled nanoparticle concentration measurement can then be directly used to quantitatively analyze the biomolecular concentration. Micro-droplets are mono-dispersed micro-reactors that can be used to encapsulate and detect AP-labeled nanoparticles. Micro-droplets include both empty micro-droplets and fluorescent micro-droplets, while fluorescent micro-droplets are generated from the fluorescence reaction between the APs adhering to a single nanoparticle and corresponding fluorogenic substrates within droplets. By detecting micro-droplets and calculating the proportion of fluorescent micro-droplets to the overall micro-droplets, we can calculate the AP-labeled nanoparticle concentration. The proposed micro-droplet detection method includes the following steps: (1) Gaussian filtering to remove the noise of overall fluorescent targets, (2) a contrast-limited, adaptive histogram equalization processing to enhance the contrast of weakly luminescent micro-droplets, (3) an red maximizing inter-class variance thresholding method (OTSU) to segment the enhanced image for getting the binary map of the overall micro-droplets, (4) a circular Hough transform (CHT) method to detect overall micro-droplets and (5) an intensity-mean-based thresholding segmentation method to extract the fluorescent micro-droplets. The experimental results of fluorescent micro-droplet images show that the average accuracy of our micro-droplet detection method is 0.9586; the average true positive rate is 0.9502; and the average false positive rate is 0.0073. The detection method can be successfully applied to measure AP-labeled nanoparticle concentration in fluorescence microscopy. Full article

In this work, we developed a facile fluorescence method for quantitative detection of human serum albumin (HSA) based on the inhibition of poly(thymine) (poly T)-templated copper nanoparticles (CuNPs) in the presence of HSA. Under normal circumstances, poly T-templated CuNPs can display strong fluorescence with excitation/emission peaks at 340/610 nm. However, in the presence of HSA, it will absorb cupric ion, which will prevent the formation of CuNPs. As a result, the fluorescence intensity will become obviously lower in the presence of HSA. The analyte HSA concentration had a proportional linear relationship with the fluorescence intensity of CuNPs. The detection limit for HSA was 8.2 × 10⁻⁸ mol·L⁻¹. Furthermore, it was also successfully employed to determine HSA in biological samples. Thus, this method has potential applications in point-of-care medical diagnosis and biomedical research. Full article

In spaceborne synthetic aperture radar (SAR) sensors, it is a challenging task to detect ground slow-moving targets against strong clutter background with limited spatial channels and restricted pulse repetition frequency (PRF). In this paper, we evaluate the image-based dual-channel SAR-ground moving target indication (SAR-GMTI) workflow for the Gaofen-3 SAR sensor and analyze the impact of strong azimuth ambiguities on GMTI when the displaced phase center antenna (DPCA) condition is not fully satisfied, which has not been demonstrated yet. An effective sliding window design technique based on system parameters analysis is proposed to deal with azimuth ambiguities and reduce false alarm. In the SAR-GMTI experiments, co-registration, clutter suppression, constant false alarm rate (CFAR) detector, vector velocity estimation and moving target relocation are analyzed and discussed thoroughly. With the real measured data of the Gaofen-3 dual-channel SAR sensor, the GMTI capability of this sensor is demonstrated and the effectiveness of the proposed method is verified. Full article

Due to their frequent use in unattended and hostile deployment environments, the security in wireless sensor networks (WSNs) has attracted much interest in the past two decades. However, it remains a challenge to design a lightweight authentication protocol for WSNs because the designers are confronted with a series of desirable security requirements, e.g., user anonymity, perfect forward secrecy, resistance to de-synchronization attack. Recently, the authors presented two authentication schemes that attempt to provide user anonymity and to resist various known attacks. Unfortunately, in this work we shall show that user anonymity of the two schemes is achieved at the price of an impractical search operation—the gateway node may search for every possible value. Besides this defect, they are also prone to smart card loss attacks and have no provision for perfect forward secrecy. As our main contribution, a lightweight anonymous authentication scheme with perfect forward secrecy is designed, and what we believe the most interesting feature is that user anonymity, perfect forward secrecy, and resistance to de-synchronization attack can be achieved at the same time. As far as we know, it is extremely difficult to meet these security features simultaneously only using the lightweight operations, such as symmetric encryption/decryption and hash functions. Full article

Surface Plasmon Resonance (SPR) is a powerful technique to study the kinetics of biomolecules undergoing biorecognition processes, particularly suited for protein-protein interactions of biomedical interest. The potentiality of SPR was exploited to sense the interactions occurring within the network of the tumor suppressor p53, which is crucial for maintaining genome integrity and whose function is inactivated, mainly by down regulation or by mutation, in the majority of human tumors. This study includes p53 down-regulators, p53 mutants and also the p53 family members, p63 and p73, which could vicariate p53 protective function. Furthermore, the application of SPR was extended to sense the interaction of p53 with anti-cancer drugs, which might restore p53 function. An extended review of previous published work and unpublished kinetic data is provided, dealing with the interaction between the p53 family members, or their mutants and two anticancer molecules, Azurin and its cell-penetrating peptide, p28. All the kinetic results are discussed in connection with those obtained by a complementary approach operating at the single molecule level, namely Atomic Force Spectroscopy and the related literature data. The overview of the SPR kinetic results may significantly contribute to a deeper understanding of the interactions within p53 network, also in the perspective of designing suitable anticancer drugs. Full article

Bicycle frames made of carbon fibre are extremely popular for high-performance cycling due to the stiffness-to-weight ratio, which enables greater power transfer. However, products manufactured using carbon fibre are sensitive to impact damage. Therefore, intelligent nondestructive evaluation is a required step to prevent failures and ensure a secure usage of the bicycle. This work proposes an inspection method based on active thermography, a proven technique successfully applied to other materials. Different configurations for the inspection are tested, including power and heating time. Moreover, experiments are applied to a real bicycle frame with generated impact damage of different energies. Tests show excellent results, detecting the generated damage during the inspection. When the results are combined with advanced image post-processing methods, the SNR is greatly increased, and the size and localization of the defects are clearly visible in the images. Full article

A large number of indoor positioning systems have recently been developed to cater for various location-based services. Indoor maps are a prerequisite of such indoor positioning systems; however, indoor maps are currently non-existent for most indoor environments. Construction of an indoor map by external experts excludes quick deployment and prevents widespread utilization of indoor localization systems. Here, we propose an algorithm for the automatic construction of an indoor floor plan, together with a magnetic fingerprint map of unmapped buildings using crowdsourced smartphone data. For floor plan construction, our system combines the use of dead reckoning technology, an observation model with geomagnetic signals, and trajectory fusion based on an affinity propagation algorithm. To obtain the indoor paths, the magnetic trajectory data obtained through crowdsourcing were first clustered using dynamic time warping similarity criteria. The trajectories were inferred from odometry tracing, and those belonging to the same cluster in the magnetic trajectory domain were then fused. Fusing these data effectively eliminates the inherent tracking errors originating from noisy sensors; as a result, we obtained highly accurate indoor paths. One advantage of our system is that no additional hardware such as a laser rangefinder or wheel encoder is required. Experimental results demonstrate that our proposed algorithm successfully constructs indoor floor plans with 0.48 m accuracy, which could benefit location-based services which lack indoor maps. Full article

Harmonious developments of electrical and mechanical performances are crucial for stretchable sensors in structural health monitoring (SHM) of flexible aircraft such as aerostats and morphing aircrafts. In this study, we prepared a highly durable ternary conductive nanocomposite made of polydimethylsiloxane (PDMS), carbon black (CB) and multi-walled carbon nanotubes (MWCNTs) to fabricate stretchable strain sensors. The nanocomposite has excellent electrical and mechanical properties by intensively optimizing the weight percentage of conducting fillers as well as the ratio of PDMS pre-polymer and curing agent. It was found that the nanocomposite with homogeneous hybrid filler of 1.75 wt % CB and 3 wt % MWCNTs exhibits a highly strain sensitive characteristics of good linearity, high gauge factor (GF ~ 12.25) and excellent durability over 10⁵ stretching-releasing cycles under a tensile strain up to 25% when the PDMS was prepared at the ratio of 12.5:1. A strain measurement of crack detection for the aerostats surface was also employed, demonstrating a great potential of such ternary nanocomposite used as stretchable strain sensor in SHM. Full article

The multichannel fluorescent sensor array based on nanofibrous membranes loaded with ZnS quantum dots (QDs) was created and demonstrated for the discriminative detection of explosives. The synergistic effect of the high surface-to-volume ratio of QDs, the good permeability of nanofibrous membranes and the differential response introduced by surface ligands was played by constructing the sensing array using nanofibrous membranes loaded with ZnS QDs featuring several surface ligands. Interestingly, although the fluorescence quenching of the nanofibrous membranes is not linearly related to the exposure time, the fingerprint of each explosive at different times is very similar in shape, and the fingerprints of the three explosives show different shapes. Three saturated vapors of nitroaromatic explosives could be reliably detected and discriminated by the array at room temperature. This work is the first step toward devising a monitoring system for explosives in the field of public security and defense. It could, for example, be coupled with the technology of image recognition and large data analysis for a rapid diagnostic test of explosives. This work further highlights the power of differential, multichannel arrays for the rapid and discriminative detection of a wide range of chemicals. Full article

In this paper, a novel dual band frequency reconfigurable antenna using an origami magic cube is proposed for wireless sensor network (WSN) applications. The proposed origami antenna consists of a meandered monopole folded onto three sides of the magic cube. A microstrip open-ended stub is loaded on the meandered monopole. The proposed origami magic cube can be mechanically folded and unfolded. The proposed antenna operates at 1.57 GHZ and 2.4 GHz in the folded state. In the unfolded state, the proposed antenna operates at 900 MHz and 2.3 GHz. The resonant frequency of the second band can be tunable by varying the length and position of the open stub. The origami magic cube is built on paper. Its performance is numerically and experimentally demonstrated from S-parameters and radiation patterns. The measured 10 dB impedance bandwidth of the proposed origami antenna is 18% (900–1120 MHz) and 15% (2.1–2.45 GHz) for the unfolded state and 20% (1.3–1.6 GHz) and 14% (2.3–2.5 GHz) for the folded state. The measured peak gain at 900 MHz and 2.3 GHz are 1.1 dBi and 2.32 dBi, respectively, in the unfolded state. The measured peak gain at 1.5 GHz and 2.4 GHz are 3.28 dBi and 1.98 dBi, respectively, in the folded state. Full article

Low current sensitivity and insufficient system stability are two key problems in all-fiber current sensor (AFCS) studies. In order to solve the two problems, a novel AFCS combining single-polarization single-mode (SPSM) couplers and a loop structure is presented in this paper with a design that incorporates the advantages of both SPSM couplers and a loop structure. SPSM couplers are shown to simplify the AFCS system and reduce the risk of interference, and the loop structure can enhance the current sensitivity. Both theory and experiment prove that the new AFCS can simultaneously overcome two prevalent obstacles of low current sensitivity and low stability. Full article

Detection and control of infectious diseases is a major problem, especially in developing countries. Lateral flow immunoassays can be used with great success for the detection of infectious diseases. However, for the quantification of their results an electronic reader is required. This paper presents an optimized handheld electronic reader for developing countries. It features a potentially low-cost, low-power, battery-operated device with no added optical accessories. The operation of this proof of concept device is based on measuring the reflected light from the lateral flow immunoassay and translating it into the concentration of the specific analyte of interest. Characterization of the surface of the lateral flow immunoassay has been performed in order to accurately model its response to the incident light. Ray trace simulations have been performed to optimize the system and achieve maximum sensitivity by placing all the components in optimum positions. A microcontroller enables all the signal processing to be performed on the device and a Bluetooth module allows transmission of the results wirelessly to a mobile phone app. Its performance has been validated using lateral flow immunoassays with influenza A nucleoprotein in the concentration range of 0.5 ng/mL to 200 ng/mL. Full article

In this paper, an assembled cantilever fiber touch trigger probe was developed for three-dimensional measurements of clear microstructures. The probe consists of a shaft assembled vertically to an optical fiber cantilever and a probing sphere located at the free end of the shaft. The laser is emitted from the free end of the fiber cantilever and converges on the photosensitive surface of the camera through the lens. The position shift of the light spot centroid was used to detect the performance of the optical fiber cantilever, which changed dramatically when the probing sphere touched the objects being measured. Experimental results indicated that the sensing system has sensitivities of 3.32 pixels/μm, 1.35 pixels/μm, and 7.38 pixels/μm in the x, y, and z directions, respectively, and resolutions of 10 nm, 30 nm, and 5 nm were achieved in the x, y, and z, respectively. An experiment on micro slit measurement was performed to verify the high aspect ratio measurement capability of the assembled cantilever fiber (ACF) probe and to calibrate the effective two-point diameter of the probing sphere. The two-point probe sphere diameter was found to be 174.634 μm with a standard uncertainly of 0.045 μm. Full article

This study presents a two-dimensional micro-/nanoradian angle generator (2D-MNAG) that achieves high angular displacement resolution and repeatability using a piezo-driven flexure hinge for two-dimensional deflections and three capacitive sensors for output angle monitoring and feedback control. The principal error of the capacitive sensor for precision microangle measurement is analyzed and compensated for; so as to achieve a high angle output resolution of 10 nrad (0.002 arcsec) and positioning repeatability of 120 nrad (0.024 arcsec) over a large angular range of ±4363 μrad (±900 arcsec) for the 2D-MNAG. The impact of each error component, together with the synthetic error of the 2D-MNAG after principal error compensation are determined using Monte Carlo simulation for further improvement of the 2D-MNAG. Full article