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Sensors Journal, IEEE

Issue 11 • Date Nov. 2012

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Displaying Results 1 - 25 of 37
  • Front Cover

    Page(s): C1
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  • IEEE Sensors Journal publication information

    Page(s): C2
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  • Table of contents

    Page(s): 3101 - 3102
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  • Table of contents

    Page(s): 3103 - 3104
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  • Guest Editorial - Special issue on machine olfaction

    Page(s): 3105 - 3107
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  • Biomimetic Olfactory Sensors

    Page(s): 3108 - 3112
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (522 KB) |  | HTML iconHTML  

    In this paper, we review olfactory biosensors based on biological components taken from biological olfactory systems. The strategies adopted in this paper include measuring an animal's behavioral response to chemical stimuli, using tissue- or cell-based biosensors, extracting receptor elements and coupling them to various transduction platforms, and creating sensing elements based on receptor proteins or peripheral chemical sensing elements such as odorant-binding proteins. View full abstract»

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  • New Acid Biosensor for Taste Transduction Based on Extracellular Recording of PKD Channels

    Page(s): 3113 - 3118
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    This paper describes a polycystic kidney disease-like (PKD) channel-based biosensor for the research of taste transduction by extracellular recording using a micro electrode array (MEA). PKD channels, which were recently proposed as candidates for sour sensation, are heterologously expressed in human embryo kidney-293 cells and coupled with MEA chips to serve as sensitive elements. MEA chips are used as transducers to monitor the responses of PKD channels to sour stimulations by extracellular recording in a noninvasive way for a long term. The results indicate that this biosensor can successfully record the special off-responses of PKD channels to sour stimulations. In addition, this biosensor can be used as a new tool for the functional assays of PKD channels. It is suggested that this biosensor may provide a promising alternative technique for the research of taste transduction, especially for the mechanisms of taste transduction mediated by ion channels. Furthermore, this biosensor also holds the potentials to be developed into electronic tongues for the detection of sour substances. View full abstract»

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  • Sweetener Recognition and Taste Prediction of Coke Drinks by Electronic Tongue

    Page(s): 3119 - 3123
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (624 KB) |  | HTML iconHTML  

    Natural and artificial sweetener monitoring methods are getting more important, since soft drinks with low energy play a considerable role in the market. Our objective is to describe the relevant sensory attributes and to determine the applicability of the electronic tongue to discriminate the coke drink samples with different sweeteners. Furthermore, the aim is to find a relationship between the taste attributes and measurement results received by the electronic tongue. An Alpha astree electronic tongue and a trained sensory panel are used to evaluate coke samples. Panelists found significant differences between the samples in 13 cases from the 18 sensory attributes defined previously by the consensus group. The samples are definitely distinguished by the electronic tongue. The main difference is found according to the sweetener content of the samples. The electronic tongue is able to distinguish samples containing different kinds of artificial and natural sweeteners, as well. The electronic tongue is able to predict, by the partial least squares regression method, the taste attributes of the coke drinks determined by the sensory panel with close correlation and low prediction error. View full abstract»

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  • Use of Sensors to Measure In-Mouth Salt Release During Food Chewing

    Page(s): 3124 - 3130
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (662 KB) |  | HTML iconHTML  

    Salt is released gradually during the in-mouth process when eating solid foods, that results from both chewing and salivation, which enables food breakdown and taste component release. This paper deals with the development of two sensors for the in-mouth monitoring of temperature and conductivity during mastication for the in-line analysis of electrolytes extracted by the saliva. This strategy saves a considerable amount of time, as it does not require at-line sampling and analysis using time-consuming techniques, such as high performance liquid chromatography. Sensors are developed specifically to be of a certain size, and be made up of materials compatible with in-mouth applications that would ensure a high degree of safety for panelists. These techniques for the in-line monitoring of salt release during the chewing of different types of foods displayed a rapid response, no lag time, and consistent results as a function of the differences between food samples and individuals. View full abstract»

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  • Cultured Cell-Adherable Electrochemical NO Biosensor With Fe Complex Sensor Matrix for High-Throughput Qualified Analysis

    Page(s): 3131 - 3134
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    Both the selectivity and sensitivity of electrochemical nitric oxide (NO) sensing are current problems in practical cellular NO sensing because there are several potential sources of interference in mammalian cell cultures that may disturb electrochemical NO detection. In this paper, the authors have designed and synthesized an Fe-polymer complex sensor material. The sensor material can selectively accumulate NO, and an electrode coated with this material can sense NO with both good NO selectivity and sensitivity. The authors also add mammalian cell adhesive activity to the sensor material to perform direct cell cultures on the sensor. View full abstract»

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  • Active Concentration-Independent Chemical Identification With a Tunable Infrared Sensor

    Page(s): 3135 - 3142
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1141 KB) |  | HTML iconHTML  

    This paper presents an active-sensing framework for concentration-independent identification of volatile chemicals using a tunable infrared interferometer. The framework operates in real time to generate a sequence of absorption lines that can best discriminate among a given set of chemicals. The active-sensing algorithm was previously developed to optimize temperature programs for metal-oxide chemosensors. Here, we adapt it to tune a nondispersive infrared spectroscope on the basis of a Fabry-Pérot interferometer (FPI). We also extend this framework to allow the identification of chemical samples irrespective of their concentrations. Therefore, we use nonnegative matrix factorization to create concentration-independent absorption profiles of different chemicals, and then employ linear least squares to fit sensor observations to the response profiles. We tested the framework on a simulated classification problem with 27 chemicals and compared against a passive sensing approach; the active-sensing consistently outperformed the passive sensing in terms of classification performance for various sensing budgets and at various levels of sensor noise. We also validated the approach experimentally using a commercial FPI sensor and a database of eight household chemicals. Our results show that the method can predict the sample identity irrespective of concentration. View full abstract»

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  • Selective Growth of ZnO Nanorods and Its Gas Sensor Application

    Page(s): 3143 - 3148
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    The facile sonochemical method has been used to selectively grow a ZnO nanorods sensing layer directly on an alumina substrate. The growth region of the ZnO nanorods array is precisely controlled by a pre-coated Pt/Zn seed layer on alumina substrate. No growth of ZnO nanostructure is found on the substrate without seed layer. The grown ZnO nanorods are well aligned and densely packed, with wurtzite crystal structure and flat hexagonal tip. The sensing properties of the obtained ZnO nanorods sensing layer to three kinds of toxic gases ( NH3, CO, and CH4) have been investigated. The sensing observation revealed that the selectively grown ZnO nanorods demonstrated good response, repeatability, and excellent linearity toward toxic gases. This result indicates that selective growth of ZnO nanorods directly on sensor substrate is an accessible and advantageous method for sensor fabrication. View full abstract»

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  • Controlled Synthesis of ZnO Nanostructures for Sub-ppm-Level VOC Detection

    Page(s): 3149 - 3155
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1156 KB) |  | HTML iconHTML  

    Various ZnO nanostructures, including nanoparticles, nanorods, nanotubes, and nanorings, were synthesized via a controlled synthesis by a facile sonochemical method combined with a chemical etching process. The morphology and structure of the fabricated nanomaterials were characterized by X-ray diffraction, scanning electron microscopy, and transmission electron microscopy. The sensing properties of different ZnO nanostructures toward volatile organic compounds gases at sub-ppm levels were investigated. The differences in the sensing responses of various nanostructures were compared, and reasonable mechanisms are proposed here. View full abstract»

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  • Optical Fiber Sensors Array to Identify Beverages by Their Odor

    Page(s): 3156 - 3162
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (843 KB) |  | HTML iconHTML  

    Four optical fiber sensors have been grouped in an array which is able to distinguish odors of different drinks. The sensing materials employed have been deposited onto optical fibers following the electrostatic self assembly method. The responses have been characterized in terms of reflected optical power; more specifically, the dynamic range and the recovery of each device have been used to discriminate between the samples. Data mining techniques based on the combination of principal component analysis and artificial neural networks are performed. The final system is trained to distinguish between grape juice, wine, and vinegar by using a set of one hundred samples of each one. Furthermore, the array can be located at up to 6 km away from the optical header, offering the possibility of in situ measurements. View full abstract»

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  • Chemical Sensing in Robotic Applications: A Review

    Page(s): 3163 - 3173
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1622 KB) |  | HTML iconHTML  

    Robots are generally equipped with at least several different modalities of sensors. Vision and range sensors are the most popular, especially in mobile robots. On the other hand, olfaction (or chemical sensing in general) had long been ignored in the robotics community because of the technical difficulties involved in realizing artificial olfaction on robotic platforms. Over the past two decades, however, various attempts are made to use chemical sensors in robotic applications. With the help of chemical sensors, mobile robots can follow chemical trails laid on the ground, track chemical plumes to find their sources, and build distribution maps of chemical substances. This paper is intended to present a brief history and the current trends of the research in this emerging field. View full abstract»

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  • Large-Scale Chemical Sensor Array Testing Biological Olfaction Concepts

    Page(s): 3174 - 3183
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1579 KB) |  | HTML iconHTML  

    Biological olfactory systems are characterized by a large number of sensors with broad overlapping specificities. The sensitivity and selectivity of the system may be enhanced by the huge redundancy of the olfactory receptor neurons (ORNs). A European project, NEUROCHEM, was devoted to test computational models of the olfactory system of vertebrates and insects. To test these models, a realistic artifact of the olfactory epithelium was developed as a large sensor array mimicking some features of biological ORNs, in particular, the broad and overlapping selectivity to many odors, the combinatorial response, the high level of redundancy, and the different dynamic ranges exhibited by same types of ORNs. The sensor array is composed of 16 384 elements arranged in four smaller arrays of 64 × 64 interdigitated electrodes deposited on a borosilicate substrate. To mimic the redundancy of the biological ORNs, tens of organic conductive polymers were chosen as active sensing materials because of their broad and diverse, but overlapping, specificity to different classes of volatile organic compounds. These sensors were characterized by their responses to varying concentrations of test analytes. The collected sensor data were processed with standard multivariate techniques and the results are reported in this paper. View full abstract»

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  • Toward a Miniaturized Low-Power Micromechanical Electronic Nose

    Page(s): 3184 - 3188
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    An electronic nose based on an array of vibrating doubly clamped beams is proposed. These very high aspect ratio (length/thickness) suspended resonators can be individually functionalized by applying polymer coatings with an inkjet printing approach. The absorption of volatile compounds induces a swelling of the polymers that result in axial stress formation and a shift of the resonance frequency. Furthermore, integrated piezoelectric transducers are used for both actuating the resonators, as well as monitoring their resonance frequency in an oscillator loop. This allows for detection at ppm-level concentrations of low molecular weight volatiles. More importantly, the generic resonant transducers can be individually coated with different polymers to allow for selective detection of volatile compounds. Here, we present the first results demonstrating the obtained selectivity by varying the coating chemistry on identical resonators. View full abstract»

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  • Signal and Data Processing for Machine Olfaction and Chemical Sensing: A Review

    Page(s): 3189 - 3214
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1245 KB) |  | HTML iconHTML  

    Signal and data processing are essential elements in electronic noses as well as in most chemical sensing instruments. The multivariate responses obtained by chemical sensor arrays require signal and data processing to carry out the fundamental tasks of odor identification (classification), concentration estimation (regression), and grouping of similar odors (clustering). In the last decade, important advances have shown that proper processing can improve the robustness of the instruments against diverse perturbations, namely, environmental variables, background changes, drift, etc. This article reviews the advances made in recent years in signal and data processing for machine olfaction and chemical sensing. View full abstract»

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  • Semi-Supervised Learning Techniques in Artificial Olfaction: A Novel Approach to Classification Problems and Drift Counteraction

    Page(s): 3215 - 3224
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1038 KB) |  | HTML iconHTML  

    Semi-supervised learning is a promising research area aiming to develop pattern recognition tools capable to exploit simultaneously the benefits from supervised and unsupervised learning techniques. These can lead to a very efficient usage of the limited number of supervised samples achievable in many artificial olfaction problems like distributed air quality monitoring. We believe it can also be beneficial in addressing another source of limited knowledge we have to face when dealing with real world problems: concept and sensor drifts. In this paper we describe the results of two artificial olfaction investigations that show semi-supervised learning techniques capabilities to boost performance of state-of-the art classifiers and regressors. The use of semi-supervised learning approach resulted in the effective reduction of drift-induced performance degradation in long-term on-field continuous operation of chemical multisensory devices. View full abstract»

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  • Odor Approximation Using Mass Spectrometry

    Page(s): 3225 - 3231
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    Since a set of odor components that can cover a wide range of smells have not been yet revealed, we studied a selection of odor components using an essential-oil mass spectrum database. Basis vectors were extracted using the nonnegative matrix factorization method, and then the nonnegative least-squares method was used to determine the recipe. The odor approximations of the three typical essential oils were evaluated by a sensory test. It was found that the mass spectrum data were correlated with the sensory test results. Moreover, this correlation was particularly high in the high m/z region. View full abstract»

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  • Electronic Noses as Flexible Tools to Assess Food Quality and Safety: Should We Trust Them?

    Page(s): 3232 - 3237
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    This paper presents three different applications of an electronic nose (EN) based on a metal oxide sensor array, in order to illustrate the broad spectrum of potential uses of the technique in food quality control. The following scenarios are considered: 1) the screening of a typical error that may occur during the processing of tomato pulp, which leads to sensory damage of the product; 2) the detection of microbial contamination by Alicyclobacillus spp. (ACB) affecting soft drinks; and 3) the proof of evidence of extra virgin olive oil fraudulently adulterated with hazelnut oil. In each case, the EN is able to identify the spoiled product by means of the alterations in the pattern of volatile compounds, reconstructed by principal component analysis of the sensor responses. View full abstract»

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  • Detecting and recognizing chemical targets in untrained backgrounds with temperature programmed sensors

    Page(s): 3238 - 3247
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2380 KB) |  | HTML iconHTML  

    Applications for artificial olfaction typically require analytical performance in the context of diverse backgrounds. Therefore, to deal with practical challenges posed by chemical species recognition in the presence of pre-trained and untrained backgrounds, a desirable feature is the ability to rapidly detect fresh analyte introductions (foreground odor) and segment their contributions from the foreground-background response cocktail. Here, we present a simple approach for this purpose based on the moving-window pair-wise correlation between sensor responses measured at multiple temperatures. We show that pairwise-correlation across isotherm segments can be used as a robust measure to rapidly detect chemical events (onset and offset), as well as to track and compensate for sensor baseline changes due to background variations. We demonstrate this approach for the problem of identifying three toxic industrial chemicals-ammonia, hydrogen cyanide, and chlorine-in several untrained backgrounds. Additionally, we show that the proposed scheme could be used to reduce baseline differences in response signatures between sensors of equivalent manufacture and thereby allow training and testing using different but comparable sensors. View full abstract»

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  • Effects of Neutron-Gamma Radiation on Fiber Bragg Grating Sensors: A Review

    Page(s): 3248 - 3257
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (757 KB) |  | HTML iconHTML  

    Fiber Bragg grating (FBG) sensing is currently one of the leading measurement technologies, but has made only minor inroads into nuclear diagnostics due, for the most part, to insufficient proof of survivability in these environments. This paper aims to review the current knowledge in this area, incorporating reviews of radiation-induced darkening of silica, shifts in Bragg peak, and changes to mechanical properties, while taking into account core/cladding chemistry, structure, and coating materials. In doing so, this review not only highlights the achievements of the scientific community up to the present, but more importantly, the key areas in which knowledge is still lacking and further concentrated investigation would be beneficial. View full abstract»

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  • Bridging the Collaborative Gap: Realizing the Clinical Potential of Breath Analysis for Disease Diagnosis and Monitoring–Tutorial

    Page(s): 3258 - 3270
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (668 KB) |  | HTML iconHTML  

    Exhaled breath analysis holds great promise for the development of noninvasive, frequently repeatable diagnostic and monitoring tools. For clinical breath analysis to advance beyond its current state, however, much closer multidisciplinary collaboration needs to be not only recognized but also effected. Therefore, this paper reviews the current state of clinical breath analysis from the perspective of the challenges the field faces medically (biomarker uncertainties, sampling methods, dynamics of exogenous compounds within the body, and standardization), technologically (the need for an affordable, user-friendly, real-time, point-of-care instrument for accurate identification of breath volatiles and their concentrations), biochemically (the need to link exhaled compounds with specific diseases by understanding the volatile products particular to relevant pathogenic processes), and in terms of data interpretation (quality, quantity, and complexity of data), collaboration (the need for a more integrated approach to breath analysis, including public health input), and development from research to accepted clinical use (funding challenges peculiar to the medical/technological interface, achieving standards of effectiveness and cost-effectiveness). Having thus increased awareness and aligned expectations among relevant disciplines, this paper provides a course of action for closer collaboration, better understanding, and more productive dialogue between these disciplines, including an iterative sensor development process that is integrated with clinical trials, formation of goals that transcend individual disciplines, creation of multidisciplinary research teams and a cross-disciplinary student exchange program, and collaborative funding options. View full abstract»

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  • Vibration Mode-Dependent Energy Harvesting Characteristics of Magnetoelectric Composite Cantilevers

    Page(s): 3271 - 3272
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (455 KB) |  | HTML iconHTML  

    In this letter, we simply fabricate magnetoelectric (ME) composite cantilevers through bonding 30 μm thick Metglas and 52 μm thick polyvinylidene fluoride with an epoxy, and report resonant and energy harvesting characteristics with applied DC and AC magnetic fields ranging from 0 to 3 kA/m. Generated ME voltages from a 40 mm long, 12.3 mm wide, and 112 μm thick cantilever are measured and analyzed as a function of the applied magnetic field. In our experiment, higher ME voltages are generated when both the DC and AC magnetic fields are present and the ME voltages around the second flexural bending mode are approximately five times higher than those around the first mode. The higher ME voltage with the second mode is also confirmed with finite element analysis. View full abstract»

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Aims & Scope

The IEEE Sensors Journal is a peer-reviewed, monthly online/print  journal devoted to sensors and sensing phenomena

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Meet Our Editors

Editor-in-Chief
Krikor Ozanyan
University of Manchester
Manchester, M13 9PL, U.K.