Sensors, Volume 13, Issue 8 (August 2013) – 80 articles , Pages 9549-11166

This paper presents the results of an operational nationwide burnt area mapping service realized over Greece for the years 2007–2011, through the implementation of the so-called BSM_NOA dedicated method developed at the National Observatory of Athens for post-fire recovery management. The method exploits multispectral satellite imagery, such as Landsat-TM, SPOT, FORMOSAT-2, WorldView and IKONOS. The analysis of fire size distribution reveals that a high number of fire events evolve to large and extremely large wildfires under favorable wildfire conditions, confirming the reported trend of an increasing fire-severity in recent years. Furthermore, under such conditions wildfires affect to a higher degree areas at high altitudes, threatening the existence of ecologically significant ecosystems. Finally, recent socioeconomic changes and land abandonment has resulted in the encroachment of former agricultural areas of limited productivity by shrubs and trees, resulting both in increased fuel availability and continuity, and subsequently increased burnability. Full article

Sensor network simulations require high fidelity and timing accuracy to be used as an implementation and evaluation tool. The cycle-accurate and instruction-level simulator is the known solution for these purposes. However, this type of simulation incurs a high computation cost since it has to model not only the instruction level behavior but also the synchronization between multiple sensors for their causality. This paper presents a novel technique that exploits asynchronous simulations of interrupt service routines (ISR). We can avoid the synchronization overheads when the interrupt service routines are simulated without preemption. If the causality errors occur, we devise a rollback procedure to restore the original synchronized simulation. This concept can be extended to any instruction-level sensor network simulator. Evaluation results show our method can enhance the simulation speed up to 52% in the case of our experiments. For applications with longer interrupt service routines and smaller number of preemptions, the speedup becomes greater. In addition, our simulator is 2 to 11 times faster than the well-known sensor network simulator. Full article

The design and development of textile-based strain sensors has been a focus of research and many investigators have studied this subject. This paper presents a new textile-based strain sensor design and shows the effect of base fabric parameters on its sensing properties. Sensing fabric could be used to measure articulations of the human body in the real environment. The strain sensing fabric was produced by using electronic flat-bed knitting technology; the base fabric was produced with elastomeric yarns in an interlock arrangement and a conductive yarn was embedded in this substrate to create a series of single loop structures. Experimental results show that there is a strong relationship between base fabric parameters and sensor properties. Full article

Palpation techniques are widely used in medical procedures to detect the presence of lumps or tumors in the soft breast tissues. Since these procedures are very subjective and depend on the skills of the physician, it is imperative to perform detailed a scientific study in order to develop more efficient medical sensors to measure and generate palpation parameters. In this research, we propose an optical-based, artificial palpation sensor for lesion characterization. This has been developed using a multilayer polydimethylsiloxane optical waveguide. Light was generated at the critical angle to reflect totally within the flexible and transparent waveguide. When a waveguide was compressed by an external force, its contact area would deform and cause the light to scatter. The scattered light was captured by a high-resolution camera and saved as an image format. To test the performance of the proposed system, we used a realistic tissue phantom with embedded hard inclusions. The experimental results show that the proposed sensor can detect inclusions and provide the relative value of size, depth, and Young’s modulus of an inclusion. Full article

The major problem of Wi-Fi fingerprint-based positioning technology is the signal strength fingerprint database creation and maintenance. The significant temporal variation of received signal strength (RSS) is the main factor responsible for the positioning error. A probabilistic approach can be used, but the RSS distribution is required. The Gaussian distribution or an empirically-derived distribution (histogram) is typically used. However, these distributions are either not always correct or require a large amount of data for each reference point. Double peaks of the RSS distribution have been observed in experiments at some reference points. In this paper a new algorithm based on an improved double-peak Gaussian distribution is proposed. Kurtosis testing is used to decide if this new distribution, or the normal Gaussian distribution, should be applied. Test results show that the proposed algorithm can significantly improve the positioning accuracy, as well as reduce the workload of the off-line data training phase. Full article

This work discusses a novel approach to image acquisition which improves the robustness of captured data required for 3D range measurements. By applying a pseudo-random code modulation to sequential acquisition of projected patterns the impact of environmental factors such as ambient light and mutual interference is significantly reduced. The proposed concept has been proven with an experimental range sensor based on the laser triangulation principle. The proposed design can potentially enhance the use of this principle to a variety of outdoor applications, such as autonomous vehicles, pedestrians’ safety, collision avoidance, and many other tasks, where robust real-time distance detection in real world environment is crucial. Full article

This paper presents an approach for realizing a phase difference measurement of a new gyro. A silicon micromachined gyro was mounted on rotating aircraft for aircraft attitude control. Aircraft spin drives the silicon pendulum of a gyro rotating at a high speed so that it can sense the transverse angular velocity of the rotating aircraft based on the gyroscopic precession principle when the aircraft has transverse rotation. In applications of the rotating aircraft single channel control system, such as damping in the attitude stabilization loop, the gyro signal must be kept in sync with the control signal. Therefore, the phase difference between both signals needs to be measured accurately. Considering that phase difference is mainly produced by both the micromachined part and the signal conditioning circuit, a mathematical model has been established and analyzed to determine the gyro’s phase frequency characteristics. On the basis of theoretical analysis, a dynamic simulation has been done for a case where the spin frequency is 15 Hz. Experimental results with the proposed measurement method applied to a silicon micromachined gyro driven by a rotating aircraft demonstrate that it is effective in practical applications. Measured curve and numerical analysis of phase frequency characteristic are in accordance, and the error between measurement and simulation is only 5.3%. Full article

Designing energy-efficient cognitive radio sensor networks is important to intelligently use battery energy and to maximize the sensor network life. In this paper, the problem of determining the power allocation that maximizes the energy-efficiency of cognitive radio-based wireless sensor networks is formed as a constrained optimization problem, where the objective function is the ratio of network throughput and the network power. The proposed constrained optimization problem belongs to a class of nonlinear fractional programming problems. Charnes-Cooper Transformation is used to transform the nonlinear fractional problem into an equivalent concave optimization problem. The structure of the power allocation policy for the transformed concave problem is found to be of a water-filling type. The problem is also transformed into a parametric form for which a ε-optimal iterative solution exists. The convergence of the iterative algorithms is proven, and numerical solutions are presented. The iterative solutions are compared with the optimal solution obtained from the transformed concave problem, and the effects of different system parameters (interference threshold level, the number of primary users and secondary sensor nodes) on the performance of the proposed algorithms are investigated. Full article

In some application fields, such as underwater archaeology or marine biology, there is the need to collect three-dimensional, close-range data from objects that cannot be removed from their site. In particular, 3D imaging techniques are widely employed for close-range acquisitions in underwater environment. In this work we have compared in water two 3D imaging techniques based on active and passive approaches, respectively, and whole-field acquisition. The comparison is performed under poor visibility conditions, produced in the laboratory by suspending different quantities of clay in a water tank. For a fair comparison, a stereo configuration has been adopted for both the techniques, using the same setup, working distance, calibration, and objects. At the moment, the proposed setup is not suitable for real world applications, but it allowed us to conduct a preliminary analysis on the performances of the two techniques and to understand their capability to acquire 3D points in presence of turbidity. The performances have been evaluated in terms of accuracy and density of the acquired 3D points. Our results can be used as a reference for further comparisons in the analysis of other 3D techniques and algorithms. Full article

This work analyzes several drift compensation mechanisms in wireless sensor networks (WSN). Temperature is an environmental factor that greatly affects oscillators shipped in every WSN mote. This behavior creates the need of improving drift compensation mechanisms in synchronization protocols. Using the Flooding Time Synchronization Protocol (FTSP), this work demonstrates that crystal oscillators are affected by temperature variations. Thus, the influence of temperature provokes a low performance of FTSP in changing conditions of temperature. This article proposes an innovative correction factor that minimizes the impact of temperature in the clock skew. By means of this factor, two new mechanisms are proposed in this paper: the Adjusted Temperature (AT) and the Advanced Adjusted Temperature (A2T). These mechanisms have been combined with FTSP to produce AT-FTSP and A2T-FTSP. Both have been tested in a network of TelosB motes running TinyOS. Results show that both AT-FTSP and A2T-FTSP improve the average synchronization errors compared to FTSP and other temperature-compensated protocols (Environment-Aware Clock Skew Estimation and Synchronization for WSN (EACS) and Temperature Compensated Time Synchronization (TCTS)). Full article

The execution of scientific workflows is gaining importance as more computing resources are available in the form of grid environments. The Publish/Subscribe paradigm offers well-proven solutions for sustaining distributed scenarios while maintaining the high level of task decoupling required by scientific workflows. In this paper, we propose a new model for supporting scientific workflows that improves the dissemination of control events. The proposed solution is based on the mapping of workflow tasks to the underlying Pub/Sub event layer, and the definition of interfaces and procedures for execution on brokers. In this paper we also analyze the strengths and weaknesses of current solutions that are based on existing message exchange models for scientific workflows. Finally, we explain how our model improves the information dissemination, event filtering, task decoupling and the monitoring of scientific workflows. Full article

Miniaturized thermal flow sensors have opened the doors for a large variety of new applications due to their small size, high sensitivity and low power consumption. Theoretically, very small detection limits of air velocity of some micrometers per second are achievable. However, the superimposed free convection is the main obstacle which prevents reaching these expected limits. Furthermore, experimental investigations are an additional challenge since it is difficult to generate very low flows. In this paper, we introduce a physical method, capable of generating very low flow values in the mixed convection region. Additionally, we present the sensor characteristic curves at the zero flow case and in the mixed convection region. Results show that the estimated minimum detectable air velocity by the presented method is 0.8 mm/s. The equivalent air velocity to the noise level of the sensor at the zero flow case is about 0.13 mm/s. Full article

A practical data recovery method is proposed for the strain data lost during the safety monitoring of mega columns. The analytical relations among the measured strains are derived to recover the data lost due to unexpected errors in long-term measurement during construction. The proposed technique is applied to recovery of axial strain data of a mega column in an irregular building structure during construction. The axial strain monitoring using the wireless strain sensing system was carried out for one year and five months between 23 July 2010 and 22 February 2012. During the long-term strain sensing, three different types of measurement errors occurred. Using the recovery technique, the strain data that could not be measured at different intervals in the measurement were successfully recovered. It is confirmed that the problems that may occur during long-term wireless strain sensing of mega columns during construction could be resolved through the proposed recovery method. Full article

Accelerometers, which can be installed inside a floating platform on the sea, are among the most commonly used sensors for operational ocean wave measurements. To examine the non-stationary features of ocean waves, this study was conducted to derive a wavelet spectrum of ocean waves and to synthesize sea surface elevations from vertical acceleration signals of a wave buoy through the continuous wavelet transform theory. The short-time wave features can be revealed by simultaneously examining the wavelet spectrum and the synthetic sea surface elevations. The in situ wave signals were applied to verify the practicality of the wavelet-based algorithm. We confirm that the spectral leakage and the noise at very-low-frequency bins influenced the accuracies of the estimated wavelet spectrum and the synthetic sea surface elevations. The appropriate thresholds of these two factors were explored. To study the short-time wave features from the wave records, the acceleration signals recorded from an accelerometer inside a discus wave buoy are analysed. The results from the wavelet spectrum show the evidence of short-time nonlinear wave events. Our study also reveals that more surface profiles with higher vertical asymmetry can be found from short-time nonlinear wave with stronger harmonic spectral peak. Finally, we conclude that the algorithms of continuous wavelet transform are practical for revealing the short-time wave features of the buoy acceleration signals. Full article

A vision system that can assess its own performance and take appropriate actions online to maximize its effectiveness would be a step towards achieving the long-cherished goal of imitating humans. This paper proposes a method for performing an online performance analysis of local feature detectors, the primary stage of many practical vision systems. It advocates the spatial distribution of local image features as a good performance indicator and presents a metric that can be calculated rapidly, concurs with human visual assessments and is complementary to existing offline measures such as repeatability. The metric is shown to provide a measure of complementarity for combinations of detectors, correctly reflecting the underlying principles of individual detectors. Qualitative results on well-established datasets for several state-of-the-art detectors are presented based on the proposed measure. Using a hypothesis testing approach and a newly-acquired, larger image database, statistically-significant performance differences are identified. Different detector pairs and triplets are examined quantitatively and the results provide a useful guideline for combining detectors in applications that require a reasonable spatial distribution of image features. A principled framework for combining feature detectors in these applications is also presented. Timing results reveal the potential of the metric for online applications. Full article

Vibration analysis is an effective tool for the condition monitoring and fault diagnosis of rolling element bearings. Conventional diagnostic methods are based on the stationary assumption, thus they are not applicable to the diagnosis of bearings working under varying speed. This constraint limits the bearing diagnosis to the industrial application significantly. In order to extend the conventional diagnostic methods to speed variation cases, a tacholess envelope order analysis technique is proposed in this paper. In the proposed technique, a tacholess order tracking (TLOT) method is first introduced to extract the tachometer information from the vibration signal itself. On this basis, an envelope order spectrum (EOS) is utilized to recover the bearing characteristic frequencies in the order domain. By combining the advantages of TLOT and EOS, the proposed technique is capable of detecting bearing faults under varying speeds, even without the use of a tachometer. The effectiveness of the proposed method is demonstrated by both simulated signals and real vibration signals collected from locomotive roller bearings with faults on inner race, outer race and rollers, respectively. Analyzed results show that the proposed method could identify different bearing faults effectively and accurately under speed varying conditions. Full article

A signal mass piezoelectric six-degrees-of-freedom (six-DOF) accelerometer is put forward in response to the need for health monitoring of the dynamic vibration characteristics of high grade digitally controlled machine tools. The operating principle of the piezoelectric six-degrees-of-freedom accelerometer is analyzed, and its structure model is constructed. The numerical simulation model (finite element model) of the six axis accelerometer is established. Piezoelectric quartz is chosen for the acceleration sensing element and conversion element, and its static sensitivity, static coupling interference and dynamic natural frequency, dynamic cross coupling are analyzed by ANSYS software. Research results show that the piezoelectric six-DOF accelerometer has advantages of simple and rational structure, correct sensing principle and mathematic model, good linearity, high rigidity, and theoretical natural frequency is more than 25 kHz, no nonlinear cross coupling and no complex decoupling work. Full article

Nitrogen (N) plays a key role in the plant life cycle. It is the main plant mineral nutrient needed for chlorophyll production and other plant cell components (proteins, nucleic acids, amino acids). Crop yield is affected by plant N status. Thus, the optimization of nitrogen fertilization has become the object of intense research due to its environmental and economic impact. This article focuses on reviewing current methods and techniques used to determine plant N status. Kjeldahl digestion and Dumas combustion have been used as reference methods for N determination in plants, but they are destructive and time consuming. By using spectroradiometers, reflectometers, imagery from satellite sensors and digital cameras, optical properties have been measured to estimate N in plants, such as crop canopy reflectance, leaf transmittance, chlorophyll and polyphenol fluorescence. High correlation has been found between optical parameters and plant N status, and those techniques are not destructive. However, some drawbacks include chlorophyll saturation, atmospheric and soil interference, and the high cost of instruments. Electrical properties of plant tissue have been used to estimate quality in fruits, and water content in plants, as well as nutrient deficiency, which suggests that they have potential for use in plant N determination. Full article

Most conventional gaze-tracking systems require that users look at many points during the initial calibration stage, which is inconvenient for them. To avoid this requirement, we propose a new gaze-tracking method with four important characteristics. First, our gaze-tracking system uses a large screen located at a distance from the user, who wears a lightweight device. Second, our system requires that users look at only four calibration points during the initial calibration stage, during which four pupil centers are noted. Third, five additional points (virtual pupil centers) are generated with a multilayer perceptron using the four actual points (detected pupil centers) as inputs. Fourth, when a user gazes at a large screen, the shape defined by the positions of the four pupil centers is a distorted quadrangle because of the nonlinear movement of the human eyeball. The gaze-detection accuracy is reduced if we map the pupil movement area onto the screen area using a single transform function. We overcame this problem by calculating the gaze position based on multi-geometric transforms using the five virtual points and the four actual points. Experiment results show that the accuracy of the proposed method is better than that of other methods. Full article

Eye blink is an important and inevitable artifact during scalp electroencephalogram (EEG) recording. The main problem in EEG signal processing is how to identify eye blink components automatically with independent component analysis (ICA). Taking into account the fact that the eye blink as an external source has a higher sum of correlation with frontal EEG channels than all other sources due to both its location and significant amplitude, in this paper, we proposed a method based on correlation index and the feature of power distribution to automatically detect eye blink components. Furthermore, we prove mathematically that the correlation between independent components and scalp EEG channels can be translating directly from the mixing matrix of ICA. This helps to simplify calculations and understand the implications of the correlation. The proposed method doesn’t need to select a template or thresholds in advance, and it works without simultaneously recording an electrooculography (EOG) reference. The experimental results demonstrate that the proposed method can automatically recognize eye blink components with a high accuracy on entire datasets from 15 subjects. Full article

Like the human eye, logarithmic image sensors achieve wide dynamic range easily at video rates, but, unlike the human eye, they suffer from low peak signal-to-noise-and-distortion ratios (PSNDRs). To improve the PSNDR, we propose integrating a delta-sigma analog-to-digital converter (ADC) in each pixel. An image sensor employing this architecture is designed, built and tested in 0.18 micron complementary metal-oxide-semiconductor (CMOS) technology. It achieves a PSNDR better than state-of-the-art logarithmic sensors and comparable to the human eye. As the approach concerns an array of many ADCs, we use a small-area low-power delta-sigma design. For scalability, each pixel has its own decimator. The prototype is compared to a variety of other image sensors, linear and nonlinear, from industry and academia. Full article

The quality of fibrous reinforcements used in composite materials can be monitored during the weaving process. Fibrous sensors previously developed in our laboratory, based on PEDOT:PSS, have been adapted so as to directly measure the mechanical stress on fabrics under static or dynamic conditions. The objective of our research has been to develop new sensor yarns, with the ability to locally detect mechanical stresses all along the warp or weft yarn. This local detection is undertaken inside the weaving loom in real time during the weaving process. Suitable electronic devices have been designed in order to record in situ measurements delivered by this new fibrous sensor yarn. Full article

This study evaluates if the temporal stability concept is applicable to a time series of satellite soil moisture images so to extend the common procedure of satellite image validation. The area of study is the Maqu area, which is located in the northeastern part of the Tibetan plateau. The network serves validation purposes of coarse scale (25–50 km) satellite soil moisture products and comprises 20 stations with probes installed at depths of 5, 10, 20, 40, 80 cm. The study period is 2009. The temporal stability concept is applied to all five depths of the soil moisture measuring network and to a time series of satellite-based moisture products from the Advance Microwave Scanning Radiometer (AMSR-E). The in-situ network is also assessed by Pearsons’s correlation analysis. Assessments by the temporal stability concept proved to be useful and results suggest that probe measurements at 10 cm depth best match to the satellite observations. The Mean Relative Difference plot for satellite pixels shows that a RMSM pixel can be identified but in our case this pixel does not overlay any in-situ station. Also, the RMSM pixel does not overlay any of the Representative Mean Soil Moisture (RMSM) stations of the five probe depths. Pearson’s correlation analysis on in-situ measurements suggests that moisture patterns over time are more persistent than over space. Since this study presents first results on the application of the temporal stability concept to a series of satellite images, we recommend further tests to become more conclusive on effectiveness to broaden the procedure of satellite validation. Full article

This paper describes a light-addressed electrolytic system used to perform an electrodeposition of enzyme-entrapped chitosan membranes for multiplexed enzyme-based bioassays using a digital micromirror device (DMD). In this system, a patterned light illumination is projected onto a photoconductive substrate serving as a photo-cathode to electrolytically produce hydroxide ions, which leads to an increased pH gradient. The high pH generated at the cathode can cause a local gelation of chitosan through sol-gel transition. By controlling the illumination pattern on the DMD, a light-addressed electrodeposition of chitosan membranes with different shapes and sizes, as well as multiplexed micropatterning, was performed. The effect of the illumination time of the light pattern on the dimensional resolution of chitosan membrane formation was examined experimentally. Moreover, multiplexed enzyme-based bioassay of enzyme-entrapped chitosan membranes was also successfully demonstrated through the electrodeposition of the chitosan membranes with various shapes/sizes and entrapping different enzymes. As a model experiment, glucose and ethanol were simultaneously detected in a single detection chamber without cross-talk using shape-coded chitosan membranes entrapped with glucose oxidase (GOX), peroxidase (POD), and Amplex Red (AmR) or alcohol oxidase (AOX), POD, and AmR by using same fluorescence indicator (AmR). Full article

The problem of determining the optimal geometric configuration of a sensor network that will maximize the range-related information available for multiple target positioning is of key importance in a multitude of application scenarios. In this paper, a set of sensors that measures the distances between the targets and each of the receivers is considered, assuming that the range measurements are corrupted by white Gaussian noise, in order to search for the formation that maximizes the accuracy of the target estimates. Using tools from estimation theory and convex optimization, the problem is converted into that of maximizing, by proper choice of the sensor positions, a convex combination of the logarithms of the determinants of the Fisher Information Matrices corresponding to each of the targets in order to determine the sensor configuration that yields the minimum possible covariance of any unbiased target estimator. Analytical and numerical solutions are well defined and it is shown that the optimal configuration of the sensors depends explicitly on the constraints imposed on the sensor configuration, the target positions, and the probabilistic distributions that define the prior uncertainty in each of the target positions. Simulation examples illustrate the key results derived. Full article

Metal oxide nanowires are very promising active materials for different applications, especially in the field of gas sensors. Advances in fabrication technologies now allow the preparation of nanowires on flexible substrates, expanding the potential market of the resulting sensors. The critical steps for the large-scale preparation of reliable sensing devices are the elimination of high temperatures processes and the stretchability of the entire final device, including the active material. Direct growth on flexible substrates and post-growth procedures have been successfully used for the preparation of gas sensors. The paper will summarize the procedures used for the preparation of flexible and wearable gas sensors prototypes with an overlook of the challenges and the future perspectives concerning this field. Full article

Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application. Full article

The integration of an Inertial Navigation System (INS) and the Global Positioning System (GPS) is common in mobile mapping and navigation applications to seamlessly determine the position, velocity, and orientation of the mobile platform. In most INS/GPS integrated architectures, the GPS is considered to be an accurate reference with which to correct for the systematic errors of the inertial sensors, which are composed of biases, scale factors and drift. However, the GPS receiver may produce abnormal pseudo-range errors mainly caused by ionospheric delay, tropospheric delay and the multipath effect. These errors degrade the overall position accuracy of an integrated system that uses conventional INS/GPS integration strategies such as loosely coupled (LC) and tightly coupled (TC) schemes. Conventional tightly coupled INS/GPS integration schemes apply the Klobuchar model and the Hopfield model to reduce pseudo-range delays caused by ionospheric delay and tropospheric delay, respectively, but do not address the multipath problem. However, the multipath effect (from reflected GPS signals) affects the position error far more significantly in a consumer-grade GPS receiver than in an expensive, geodetic-grade GPS receiver. To avoid this problem, a new integrated INS/GPS architecture is proposed. The proposed method is described and applied in a real-time integrated system with two integration strategies, namely, loosely coupled and tightly coupled schemes, respectively. To verify the effectiveness of the proposed method, field tests with various scenarios are conducted and the results are compared with a reliable reference system. Full article

Heart failure is a common cardiac disease in elderly patients. After discharge, approximately 50% of all patients are readmitted to a hospital within six months. Recent studies show that home monitoring of heart failure patients can reduce the number of readmissions. Still, a large number of false positive alarms as well as underdiagnoses in other cases require more accurate alarm generation algorithms. New low-cost sensors for leg edema detection could be the missing link to help home monitoring to its breakthrough. We evaluated a 3D camera-based measurement setup in order to geometrically detect and quantify leg edemas. 3D images of legs were taken and geometric parameters were extracted semi-automatically from the images. Intra-subject variability for five healthy subjects was evaluated. Thereafter, correlation of 3D parameters with body weight and leg circumference was assessed during a clinical study at the Medical University of Graz. Strong correlation was found in between both reference values and instep height, while correlation in between curvature of the lower leg and references was very low. We conclude that 3D imaging might be a useful and cost-effective extension of home monitoring for heart failure patients, though further (prospective) studies are needed. Full article

This paper presents a project on the development of a cursor control emulating the typical operations of a computer-mouse, using gyroscope and eye-blinking electromyographic signals which are obtained through a commercial 16-electrode wireless headset, recently released by Emotiv. The cursor position is controlled using information from a gyroscope included in the headset. The clicks are generated through the user’s blinking with an adequate detection procedure based on the spectral-like technique called Empirical Mode Decomposition (EMD). EMD is proposed as a simple and quick computational tool, yet effective, aimed to artifact reduction from head movements as well as a method to detect blinking signals for mouse control. Kalman filter is used as state estimator for mouse position control and jitter removal. The detection rate obtained in average was 94.9%. Experimental setup and some obtained results are presented. Full article