Changes in the chemical environment can trigger large motions in chemomechanical polymers. The unique feature of such intelligent materials, mostly in the form of hydrogels, is therefore, that they serve as sensors and actuators at the same time, and do not require any measuring devices, transducers or power supplies. Until recently the most often used of these materials responded to changes in pH. Chemists are now increasingly using supramolecular recognition sites in materials, which are covalently bound to the polymer backbone. This allows one to use a nearly unlimited variety of guest (or effector) compounds in the environment for a selective response by automatically triggered size changes. This is illustrated with non-covalent interactions of effectors comprising of metal ions, isomeric organic compounds, including enantiomers, nucleotides, aminoacids, and peptides. Two different effector molecules can induce motions as functions of their concentration, thus representing a logical AND gate. This concept is particularly fruitful with effector compounds such as peptides, which only trigger size changes if, e.g. copper ions are present in the surroundings. Another principle relies on the fast formation of covalent bonds between an effector and the chemomechanical polymer. The most promising application is the selective interaction of covalently fixed boronic acid residues with glucose, which renders itself not only for sensing, but eventually also for delivery of drugs such as insulin. The speed of the responses can significantly increase by increasing the surface to volume ratio of the polymer particles. Of particular interest is the sensitivity increase which can be reached by downsizing the particle volume.
chemomechanical polymers; hydrogels; molecular recognition; supramolecular complexes; artificial muscles; glucose sensors
Tip-enhanced Raman spectroscopy (TERS) is used to investigate the influence of strains in isolated and overlapping silicon nanowires prepared by chemical etching of a (100) silicon wafer. An atomic force microscopy tip made of nanocrystalline diamond coated with a thin layer of silver is used in conjunction with an excitation wavelength of 532 nm in order to probe the first order optical phonon mode of the  silicon nanowires. The frequency shift and the broadening of the silicon first order phonon are analyzed and compared to the topographical measurements for distinct configuration of nanowires that are disposed in straight, bent or overlapping configuration over a microscope coverslip. The TERS spatial resolution is close to the topography provided by the nanocrystalline diamond tip and subtle spectral changes are observed for different nanowire configurations.
tip-enhanced Raman spectroscopy; atomic force microscopy; silicon nanowires; strain/stress-induced broadening
The study investigates the fabrication and characterization of an ethanol microsensor equipped with a heater. The ethanol sensor is manufactured using the commercial 0.18 μm complementary metal oxide semiconductor (CMOS) process. The sensor consists of a sensitive film, a heater and interdigitated electrodes. The sensitive film is zinc oxide prepared by the sol-gel method, and it is coated on the interdigitated electrodes. The heater is located under the interdigitated electrodes, and it is used to supply a working temperature to the sensitive film. The sensor needs a post-processing step to remove the sacrificial oxide layer, and to coat zinc oxide on the interdigitated electrodes. When the sensitive film senses ethanol gas, the resistance of the sensor generates a change. An inverting amplifier circuit is utilized to convert the resistance variation of the sensor into the output voltage. Experiments show that the sensitivity of the ethanol sensor is 0.35 mV/ppm.
ethanol sensor; zinc oxide film; heater; post-process
An optical flow-based technique is proposed to estimate spacecraft angular velocity based on sequences of star-field images. It does not require star identification and can be thus used to also deliver angular rate information when attitude determination is not possible, as during platform de tumbling or slewing. Region-based optical flow calculation is carried out on successive star images preprocessed to remove background. Sensor calibration parameters, Poisson equation, and a least-squares method are then used to estimate the angular velocity vector components in the sensor rotating frame. A theoretical error budget is developed to estimate the expected angular rate accuracy as a function of camera parameters and star distribution in the field of view. The effectiveness of the proposed technique is tested by using star field scenes generated by a hardware-in-the-loop testing facility and acquired by a commercial-off-the shelf camera sensor. Simulated cases comprise rotations at different rates. Experimental results are presented which are consistent with theoretical estimates. In particular, very accurate angular velocity estimates are generated at lower slew rates, while in all cases the achievable accuracy in the estimation of the angular velocity component along boresight is about one order of magnitude worse than the other two components.
spacecraft angular velocity estimation; star field images; optical flow; performance analysis; hardware-in-the-loop simulation
In this study a novel sensitive nanogold particle sensor enhancement based on mixed self-assembled monolayers was explored and used to construct a Surface Plasmon Resonance (SPR) immunosensor to detect Ischemia Modified Albumin (IMA). Compared with a direct binding SPR assay at a limit of detection (LOD) of 100 ng/L, gold nanoparticles (AuNPs) of 10 nm dramatically improved the LOD of IMA to 10 ng/L. Meanwhile, no interfering substance that may lead to false positive results was identified. These results suggested that the SPR biosensor presented superior properties, and provided a simple label-free strategy to increase assay sensitivity for further acute coronary syndrome (ACS) diagnosis.
ischemia modified albumin; surface plasmon resonance immunosensor; gold nanoparticles; signal enhancement
This paper presents a novel three-dimensional (3D) multi-spectrum sensor system, which combines a 3D depth sensor and multiple optical sensors for different wavelengths. Various image sensors, such as visible, infrared (IR) and 3D sensors, have been introduced into the commercial market. Since each sensor has its own advantages under various environmental conditions, the performance of an application depends highly on selecting the correct sensor or combination of sensors. In this paper, a sensor system, which we will refer to as a 3D multi-spectrum sensor system, which comprises three types of sensors, visible, thermal-IR and time-of-flight (ToF), is proposed. Since the proposed system integrates information from each sensor into one calibrated framework, the optimal sensor combination for an application can be easily selected, taking into account all combinations of sensors information. To demonstrate the effectiveness of the proposed system, a face recognition system with light and pose variation is designed. With the proposed sensor system, the optimal sensor combination, which provides new effectively fused features for a face recognition system, is obtained.
image sensor; depth sensor; sensor fusion; face recognition
In the face recognition field, principal component analysis is essential to the reduction of the image dimension. In spite of frequent use of this analysis, it is commonly believed that the basis faces with large eigenvalues are chosen as the best subset in the nearest neighbor classifiers. We propose an alternative that can predict the classification error during the training steps and find the useful basis faces for the similarity metrics of the classical pattern algorithms. In addition, we also show the need for the eye-aligned dataset to have the pure face. The experiments using face images verify that our method reduces the negative effect on the misaligned face images and decreases the weights of the useful basis faces in order to improve the classification accuracy.
feature selection; similarity metrics; learning weights
Automated methods of real-time, unobtrusive, human ambulation, activity, and wellness monitoring and data analysis using various algorithmic techniques have been subjects of intense research. The general aim is to devise effective means of addressing the demands of assisted living, rehabilitation, and clinical observation and assessment through sensor-based monitoring. The research studies have resulted in a large amount of literature. This paper presents a holistic articulation of the research studies and offers comprehensive insights along four main axes: distribution of existing studies; monitoring device framework and sensor types; data collection, processing and analysis; and applications, limitations and challenges. The aim is to present a systematic and most complete study of literature in the area in order to identify research gaps and prioritize future research directions.
sensor-based monitoring; sensor placement; monitoring device framework; data collection and processing; gait assessment/fall risk estimation
This paper presents a bio-inspired networking strategy to support the cooperation between static sensors on the ground and mobile sensors in the air to perform surveillance missions in large areas. The goal of the proposal is to provide low overhead in the communication among sensor nodes, while allocating the mobile sensors to perform sensing activities requested by the static ones. Simulations have shown that the strategy is efficient in maintaining low overhead and achieving the desired coordination.
wireless sensor network coordination; bio-inspired networking; mobile sensor nodes; surveillance systems
Automatic detection of pig wasting diseases is an important issue in the management of group-housed pigs. Further, respiratory diseases are one of the main causes of mortality among pigs and loss of productivity in intensive pig farming. In this study, we propose an efficient data mining solution for the detection and recognition of pig wasting diseases using sound data in audio surveillance systems. In this method, we extract the Mel Frequency Cepstrum Coefficients (MFCC) from sound data with an automatic pig sound acquisition process, and use a hierarchical two-level structure: the Support Vector Data Description (SVDD) and the Sparse Representation Classifier (SRC) as an early anomaly detector and a respiratory disease classifier, respectively. Our experimental results show that this new method can be used to detect pig wasting diseases both economically (even a cheap microphone can be used) and accurately (94% detection and 91% classification accuracy), either as a standalone solution or to complement known methods to obtain a more accurate solution.
pig wasting diseases; sound data; mel frequency cepstrum coefficient; support vector data description; sparse representation classifier
Proteobacteria produce N-acylhomoserine lactones as signaling molecules, which will bind to their cognate receptor and activate quorum sensing-mediated phenotypes in a population-dependent manner. Although quorum sensing signaling molecules can be degraded by bacteria or fungi, there is no reported work on the degradation of such molecules by basidiomycetous yeast. By using a minimal growth medium containing N-3-oxohexanoylhomoserine lactone as the sole source of carbon, a wetland water sample from Malaysia was enriched for microbial strains that can degrade N-acylhomoserine lactones, and consequently, a basidiomycetous yeast strain WW1C was isolated. Morphological phenotype and molecular analyses confirmed that WW1C was a strain of Trichosporon loubieri. We showed that WW1C degraded AHLs with N-acyl side chains ranging from 4 to 10 carbons in length, with or without oxo group substitutions at the C3 position. Re-lactonisation bioassays revealed that WW1C degraded AHLs via a lactonase activity. To the best of our knowledge, this is the first report of degradation of N-acyl-homoserine lactones and utilization of N-3-oxohexanoylhomoserine as carbon and nitrogen source for growth by basidiomycetous yeast from tropical wetland water; and the degradation of bacterial quorum sensing molecules by an eukaryotic yeast.
basidiomycetous; biosensor; lactonase; N-acylhomoserine lactone; quorum sensing; quorum quenching; Rapid Resolution Liquid Chromatography; Trichosporon loubieri; yeast
Shape memory alloy (SMA) has great potential to develop light and compact artificial muscle (AM) due to its muscle-like high power-to-weight ratio, flexibility and silent operation properties. In this paper, SMA self-sensing properties are explored and modeled in depth to imitate the integrated muscle-like functions of actuating and self-sensing for SMA-AM based on the investigation of SMA electrical resistivity (ER). Firstly, an ER transformation kinetics model is proposed based on the simulation of SMA differential scanning calorimetry (DSC) curves. Then a series of thermal-electrical-mechanical experiments are carried out to verify the validity of the ER model, whereby the SMA-AM self-sensing function is well established under different stress conditions. Finally the self-sensing capability is further demonstrated by its application to a novel SMA-AM-actuated active ankle-foot orthosis (AAFO).
shape memory alloy; artificial muscle; self-sensing model; electrical resistivity; active ankle-foot orthosis
We describe a novel microarray based-method for the screening of oncogenic human papillomavirus 18 (HPV-18) molecular variants. Due to the fact that sequencing methodology may underestimate samples containing more than one variant we designed a specific and sensitive stacking DNA hybridization assay. This technology can be used to discriminate between three possible phylogenetic branches of HPV-18. Probes were attached covalently on glass slides and hybridized with single-stranded DNA targets. Prior to hybridization with the probes, the target strands were pre-annealed with the three auxiliary contiguous oligonucleotides flanking the target sequences. Screening HPV-18 positive cell lines and cervical samples were used to evaluate the performance of this HPV DNA microarray. Our results demonstrate that the HPV-18's variants hybridized specifically to probes, with no detection of unspecific signals. Specific probes successfully reveal detectable point mutations in these variants. The present DNA oligoarray system can be used as a reliable, sensitive and specific method for HPV-18 variant screening. Furthermore, this simple assay allows the use of inexpensive equipment, making it accessible in resource-poor settings.
HPV-18; microarray; variants; LCR
A fluorescent molecularly imprinted nanosensor was obtained by grafting imprinted polymer onto the surface of multi-wall carbon nanotubes and post-imprinting treatment with fluorescein isothiocyanate (FITC). The fluorescence of lysozyme-imprinted polymer (Lys-MIP) was quenched more strongly by Lys than that of nonimprinted polymer (NIP), which indicated that the Lys-MIP could recognize Lys. The resulted imprinted material has the ability to selectively sense a target protein, and an imprinting factor of 3.34 was achieved. The Lys-MIP also showed selective detection for Lys among other proteins such as cytochrome C (Cyt C), hemoglobin (HB) and bovine serum albumin (BSA) due to the imprinted sites in the Lys-MIP. This approach combines the high selectivity of surface molecular imprinting technology and fluorescence, and converts binding events into detectable signals by monitoring fluorescence spectra. Therefore, it will have further applications for Lys sensing.
molecularly imprinted polymers; protein; fluorescent sensing
Interest in the cognitive radio sensor network (CRSN) paradigm has gradually grown among researchers. This concept seeks to fuse the benefits of dynamic spectrum access into the sensor network, making it a potential player in the next generation (NextGen) network, which is characterized by ubiquity. Notwithstanding its massive potential, little research activity has been dedicated to the network layer. By contrast, we find recent research trends focusing on the physical layer, the link layer and the transport layers. The fact that the cross-layer approach is imperative, due to the resource-constrained nature of CRSNs, can make the design of unique solutions non-trivial in this respect. This paper seeks to explore possible design opportunities with wireless sensor networks (WSNs), cognitive radio ad-hoc networks (CRAHNs) and cross-layer considerations for implementing viable CRSN routing solutions. Additionally, a detailed performance evaluation of WSN routing strategies in a cognitive radio environment is performed to expose research gaps. With this work, we intend to lay a foundation for developing CRSN routing solutions and to establish a basis for future work in this area.
ad-hoc networks; cognitive radio; cross-layer; wireless sensor network; routing
Ferulic acid is an important phenolic antioxidant found in or added to diet supplements, beverages, and cosmetic creams. Two designs of paper-based platforms for the fast, simple and inexpensive evaluation of ferulic acid contents in food and pharmaceutical cosmetics were evaluated. The first, a paper-based electrochemical device, was developed for ferulic acid detection in uncomplicated matrix samples and was created by the photolithographic method. The second, a paper-based colorimetric device was preceded by thin layer chromatography (TLC) for the separation and detection of ferulic acid in complex samples using a silica plate stationary phase and an 85:15:1 (v/v/v) chloroform: methanol: formic acid mobile phase. After separation, ferulic acid containing section of the TLC plate was attached onto the patterned paper containing the colorimetric reagent and eluted with ethanol. The resulting color change was photographed and quantitatively converted to intensity. Under the optimal conditions, the limit of detection of ferulic acid was found to be 1 ppm and 7 ppm (S/N = 3) for first and second designs, respectively, with good agreement with the standard HPLC-UV detection method. Therefore, these methods can be used for the simple, rapid, inexpensive and sensitive quantification of ferulic acid in a variety of samples.
ferulic acid; paper-based platforms; electrochemical detection; colorimetric detection; TLC separation
Previous research has indicated that viewing 3D displays may induce greater visual fatigue than viewing 2D displays. Whether viewing 3D displays can evoke measureable emotional responses, however, is uncertain. In the present study, we examined autonomic nervous system responses in subjects viewing 2D or 3D displays. Autonomic responses were quantified in each subject by heart rate, galvanic skin response, and skin temperature. Viewers of both 2D and 3D displays showed strong positive correlations with heart rate, which indicated little differences between groups. In contrast, galvanic skin response and skin temperature showed weak positive correlations with average difference between viewing 2D and 3D. We suggest that galvanic skin response and skin temperature can be used to measure and compare autonomic nervous responses in subjects viewing 2D and 3D displays.
visual fatigue; autonomic nervous system; heart rate; galvanic skin response; skin temperature
In this study, reduced graphene oxide (rGO) was electrochemically deposited on the surface of screen-printed carbon electrodes (SPCE) to prepare a disposable sensor for fast detection of Pb2+ in foods. The SEM images showed that the rGO was homogeneously deposited onto the electrode surface with a wrinkled nanostructure, which provided 2D bridges for electron transport and a larger active area for Pb2+ adsorption. Results showed that rGO modification enhanced the activity of the electrode surface, and significantly improved the electrochemical properties of SPCE. The rGO modified SPCE (rGO-SPCE) was applied to detect Pb2+ in standard aqueous solution, showing a sharp stripping peak and a relatively constant peak potential in square wave anodic stripping voltammetry (SWASV). The linear range for Pb2+ detection was 5∼200 ppb (R2 = 0.9923) with a low detection limit of 1 ppb (S/N = 3). The interference of Cd2+ and Cu2+ at low concentrations was effectively avoided. Finally, the rGO-SPCE was used for determination of lead in real tap water, juice, preserved eggs and tea samples. Compared with results from graphite furnace atomic absorption spectroscopy (GFAAS), the results based on rGO-SPCE were both accurate and reliable, suggesting that the disposable sensor has great potential in application for fast, sensitive and low-cost detection of Pb2+ in foods.
reduced graphene oxide (rGO); electrochemical deposition; screen-printed carbon electrode (SPCE); square wave voltammetry; Pb2+
The design and development of a plastic optical fiber (POF) macrobend temperature sensor is presented. The sensor has a linear response versus temperature at a fixed bend radius, with a sensitivity of 1.92·10−3 (°C)−1. The sensor system used a dummy fiber-optic sensor for reference purposes having a resolution below 0.3 °C. A comprehensive experimental analysis was carried out to provide insight into the effect of different surrounding media on practical macro-bend POF sensor implementation. Experimental results are successfully compared with bend loss calculations.
polymer optical fiber sensor; temperature; intensity; bend loss; metal surface
This paper presents a method implemented in a system for automatic contactless calibration of gauge blocks designed at ISI ASCR. The system combines low-coherence interferometry and laser interferometry, where the first identifies the gauge block sides position and the second one measures the gauge block length itself. A crucial part of the system is the algorithm for gauge block alignment to the measuring beam which is able to compensate the gauge block lateral and longitudinal tilt up to 0.141 mrad. The algorithm is also important for the gauge block position monitoring during its length measurement.
low-coherence interferometry; gauge block; metrology
Smartphone-based activity recognition (SP-AR) recognizes users' activities using the embedded accelerometer sensor. Only a small number of previous works can be classified as online systems, i.e., the whole process (pre-processing, feature extraction, and classification) is performed on the device. Most of these online systems use either a high sampling rate (SR) or long data-window (DW) to achieve high accuracy, resulting in short battery life or delayed system response, respectively. This paper introduces a real-time/online SP-AR system that solves this problem. Exploratory data analysis was performed on acceleration signals of 6 activities, collected from 30 subjects, to show that these signals are generated by an autoregressive (AR) process, and an accurate AR-model in this case can be built using a low SR (20 Hz) and a small DW (3 s). The high within class variance resulting from placing the phone at different positions was reduced using kernel discriminant analysis to achieve position-independent recognition. Neural networks were used as classifiers. Unlike previous works, true subject-independent evaluation was performed, where 10 new subjects evaluated the system at their homes for 1 week. The results show that our features outperformed three commonly used features by 40% in terms of accuracy for the given SR and DW.
accelerometer sensor; smartphone; context-awareness; activity recognition; expolatory data analysis; feature extraction
DC-offset and DC-suppression are key parameters in bioelectric amplifiers. However, specific DC analyses are not often explained. Several factors influence the DC-budget: the programmable gain, the programmable cut-off frequencies for high pass filtering and, the low cut-off values and the capacitor blocking issues involved. A new intermediate stage is proposed to address the DC problem entirely. Two implementations were tested. The stage is composed of a programmable gain amplifier (PGA) with DC-rejection and low output offset. Cut-off frequencies are selectable and values from 0.016 to 31.83 Hz were tested, and the capacitor deblocking is embedded in the design. Hence, this PGA delivers most of the required gain with constant low output offset, notwithstanding the gain or cut-off frequency selected.
bioelectric sensors; biomedical electronics; amplifiers; high-pass filters
This article deals with the application of the principles of SCD (Selective Change Driven) vision to 3D laser scanning. Two experimental sets have been implemented: one with a classical CMOS (Complementary Metal-Oxide Semiconductor) sensor, and the other one with a recently developed CMOS SCD sensor for comparative purposes, both using the technique known as Active Triangulation. An SCD sensor only delivers the pixels that have changed most, ordered by the magnitude of their change since their last readout. The 3D scanning method is based on the systematic search through the entire image to detect pixels that exceed a certain threshold, showing the SCD approach to be ideal for this application. Several experiments for both capturing strategies have been performed to try to find the limitations in high speed acquisition/processing. The classical approach is limited by the sequential array acquisition, as predicted by the Nyquist–Shannon sampling theorem, and this has been experimentally demonstrated in the case of a rotating helix. These limitations are overcome by the SCD 3D scanning prototype achieving a significantly higher performance. The aim of this article is to compare both capturing strategies in terms of performance in the time and frequency domains, so they share all the static characteristics including resolution, 3D scanning method, etc., thus yielding the same 3D reconstruction in static scenes.
event-based vision; high-speed visual acquisition; 3D scanning
A novel approach for identifying explosive species is reported, using Raman spectroscopy in suspended core optical fibers. Numerical simulations are presented that predict the strength of the observed signal as a function of fiber geometry, with the calculated trends verified experimentally and used to optimize the sensors. This technique is used to identify hydrogen peroxide in water solutions at volumes less than 60 nL and to quantify microgram amounts of material using the solvent's Raman signature as an internal calibration standard. The same system, without further modifications, is also used to detect 1,4-dinitrobenzene, a model molecule for nitrobenzene-based explosives such as 2,4,6-trinitrotoluene (TNT).
explosives detection; fiber sensors; Raman spectroscopy; chemical sensing; microstructured optical fibers
Presented here is a slotted-quad-beam structure sensor for the measurement of friction in micro bearings. Stress concentration slots are incorporated into a conventional quad-beam structure to improve the sensitivity of force measurements. The performance comparison between the quad-beam structure sensor and the slotted-quad-beam structure sensor are performed by theoretical modeling and finite element (FE) analysis. A hollow stainless steel probe is attached to the mesa of the sensor chip by a tailor-made organic glass fixture. Concerning the overload protection of the fragile beams, a glass wafer is bonded onto the bottom of sensor chip to limit the displacement of the mesa. The calibration of the packaged device is experimentally performed by a tri-dimensional positioning stage, a precision piezoelectric ceramic and an electronic analytical balance, which indicates its favorable sensitivity and overload protection. To verify the potential of the proposed sensor being applied in micro friction measurement, a measurement platform is established. The output of the sensor reflects the friction of bearing resulting from dry friction and solid lubrication. The results accord with the theoretical modeling and demonstrate that the sensor has the potential application in measuring the micro friction force under stable stage in MEMS machines.
micro-force sensor; stress concentration slots; friction measurement