This paper presents a multi-feature approach for detection of key postures by using a MESA SR4000 time-offlight 3D sensor managed by a low-power embedded PC. Acquired data were pre-processed by using a well-established framework including self-calibration, segmentation and tracking functionalities. To accommodate different application scenarios, hierarchical coarse-to-fine features were extracted by exploiting two different descriptors: topological and volumetric. The topological descriptor encoded intrinsic topology of body postures in a skeleton-like representation based on geodesic distance. Instead, the volumetric descriptor used a cylindrical voxelization to describe postures in a histogram-based representation. Both synthetic and real datasets were used to evaluate performance. The complementary discrimination capabilities exhibited by the two descriptors allowed to achieve good results in four different application scenarios with a classification rate greater than 96.4%. © 2012 IEEE.

The aging population represents an emerging challenge for healthcare since elderly people frequently suffer from chronic diseases requiring continuous medical care and monitoring. Sensor networks are possible enabling technologies for ambient assisted living solutions helping elderly people to be independent and to feel more secure. This paper presents a multi-sensor system for the detection of people falls in home environment. Two kinds of sensors are used: a wearable wireless accelerometer with onboard fall detection algorithms and a time-of-flight camera. A coordinator node receives data from the two sub-sensory systems with their associated level of confidence and, on the basis of a data fusion logic, it operates the validation and correlation among the two sub-systems delivered data in order to rise overall system performance with respect to each single sensor sub-system. Achieved results show the effectiveness of the suggested multisensor approach for improving fall detection service in ambient assisted living contexts.

Purpose: Although no cure is available, cognitive rehabilitation (CR) for patients with mild¹ Alzheimer's disease (AD) appears to be an attractive treatment. In the last two years many technical solutions, such as serious games, have been studied for cognitive assistance^2,3. However, most of these initiatives (including commercial products such as Nintendo's Brain Age and Big Brain Academy) provide only memory challenges or random puzzles that are to be played a few minutes per day with the purpose of "improving brain performance". The objective of this work is the design and development of an Information and Communication Technology (ICT) platform that integrates advanced Natural User Interface (NUI) technologies for multi-domain cognitive rehabilitation (temporal and spatial orientation, visual and topographical memory, verbal memory and fluency, visual and hearing attention, etc.). Method: The platform architecture (Figure 1) is made up of a) a set-top-box connected to a TV monitor with internet connection, b) a commercial low-cost RGB-D camera (Microsoft Kinect), and c) an (optional) e-shirt (WWS Smartex) for monitoring vital signs. According to the specific rehabilitation program provided by the physician, the set-top-box automatically downloads customized sequences of exercises from a remote server, taking into account the patient's rehabilitation history and related factors. In order to make the system reliable, flexible, customized, and compliant with the international evaluation scales (MMSE: Mini Mental Scale Evaluation), few input parameters (amount of allowed errors and execution time, movement sensitivity) are set, and these parameters are based on the residual abilities of the patient. The system allows both autonomous execution of the required exercises and data reporting and storing of the daily performance for every exercise. In order to obtain more information during rehabilitation activities, the main vital signs (heart rate, breathing rate, electrocardiogram, etc.) are monitored if the subject wears the (optional) e-shirt. A Bluetooth radio link is used for transmitting clinical parameters to the set-top-box. Results & Discussion: The platform allows CR for AD patients without direct physician involvement in the rehabilitation session. (Performance metrics and clinical parameters are sent to the physician with a multimodal paradigm for clinical evaluations.) For proper interaction with the system, measurements from the patient are acquired by the RGB-D sensor at a distance range between 80 cm and 400 cm, allowing Natural User Interaction through 100% hands detection rate (Figure 2). The system allows an audiovisual link with the medical center, so that the physician can interact with the AD patient during CR, increasing the compliance and efficacy of CR and ensuring that the type and intensity of treatment are appropriate.

In this work, a novel data analysis method for the exploitation of semiconductor metal-oxide-based detectors in chromatographic systems is presented and evaluated. The method exploits the properties of the detector response in the time domain for increasing the time resolution of chromatograms measured with gas sensors. The performances in terms of sensitivity and response speed of a microfabricated Cr-doped WO3 sensor array have been compared against a state-of-the-art mass spectrometer detector in order to validate the method in a demanding application such as the determination of the content of volatile organic compounds in wines.

The paper presents a wearable system able to evaluate real time the risk of fall in elderly people, promoting the fast adoption of properly intervention strategies for reducing injuries (e.g. by activating an impact reduction system). A wireless and minimally invasive surface Electromyography-based system (EMG) has been used to measure four lower limb muscles activities. This work deals with the identification of highly discriminative features extracted from the EMG signals for the automatic detection of people instability. The framework prototype uses a threshold-based approach assuring real time functioning and permitting the detection of a typical imbalance condition about 200ms after the stimulus perturbation, in simulated and controlled fall conditions.

One distinctive feature of ambient assisted living-oriented systems is the ability to provide assistive services in smart environments as elderly people need in their daily life. Since Time-Of-Flight vision technologies are increasingly investigated as monitoring solution able to outperform traditional approaches, in this work a monitoring framework based on a Time-Of-Flight sensor network has been investigated with the aim to provide a wide-range solution suitable in several assisted living scenarios. Detector nodes are managed by a low-power embedded PC to process Time-Of-Flight streams and extract features related with person's activities. The feature level of detail is tuned in an application-driven manner in order to optimize both bandwidth and computational resources. The event detection capabilities were validated by using data collected in real-home environments.

Cognitive Rehabilitation (CR) is a relatively new approach to improve well-being for people with Alzheimer's disease (AD). At present only preliminary evidence regarding efficacy is available but it is enough to suggest that this kind of rehabilitation has the potential to bring about changes in behavior, enhance well-being and maintain involvement in daily life. The present work presents a digital platform integrating Natural User Interface (NUI) for motor and cognitive rehabilitation of patients with different disease condition. It is made up of an embedded PC connected to a TV monitor with internet connection, a low-cost 3D sensor (we use Microsoft Kinect in order to allow wide diffusion of the proposed solution), and an optional e-shirt with textile electrodes for clinical signs detection. The main contribution of this work is the design and implementation of an information and communication technologies (ICT) platform, through a customized Virtual Personal Trainer (VPT) allowing the patients to perform the rehabilitation practice at home. Moreover, the system provides an audio/visual link with the medical center, so the physician can interact with the patient during the rehabilitation practice, increasing the compliance and the efficacy and making sure that the type and intensity of treatment are appropriate. Customized algorithms for calibration, people segmentation, body skeletonization and hands tracking through the Kinect sensor have been implemented in order to infer knowledge about the reaction of the end-user to the Graphical User Interface (GUI) designedfor specific cognitive domains. For proper interaction, gestures of AD patients are acquired by the sensor in the nominal functioning range, allowing 100% hands detection rate, useful for an error free human-machine.

In this work we develop surface-micromachinedRF MEMS switches in III-V technology making use ofmaterials which can be alternative to the ones commonly used.In this way, some technological constraints concerning RFMEMS reliability can be overcome. Specifically, we evaluatethe potential of tantalum nitride (TaN) and tantalumpentoxide (Ta2O5) to be used for the switches actuation padsand dielectric layers, respectively. To this scope, acompositional, structural and electrical characterization ofTaN and Ta2O5 films as a function of the depositionparameters (temperature, sputtering mixture composition, andfilm thickness) is performed. Both shunt and series switchesare prepared and show good switching capabilities by apreliminary analysis. The complete device characterization isin progress and will be presented.

The paper presents an active vision system for the automatic detection of falls and the recognition of several postures for elderly homecare applications. A wall-mounted Time-Of-Flight camera provides accurate measurements of the acquired scene in all illumination conditions, allowing the reliable detection of critical events. Preliminarily, an off-line calibration procedure estimates the external camera parameters automatically without landmarks, calibration patterns or userintervention. The calibration procedure searches for different planes in the scene selecting the one that accomplishes the floor plane constraints. Subsequently, the moving regions are detected in real-time by applying a Bayesian segmentation to the whole 3D points cloud. The distance of the 3D human centroid from thefloor plane is evaluated by using the previously defined calibration parameters and the corresponding trend is used as feature in a thresholding-based clustering for fall detection. The fall detection shows high performances in terms of efficiency and reliability on a large real dataset in which almost one half of events are falls acquired in different conditions. The posture recognition is carried out by using both the 3D human centroid distance from the floor plane and the orientation of the body spine estimated by applying a topological approach to the range images. Experimental results on synthetic data validate the correctness of the proposed posture recognition approach.

The paper presents an active vision system for the detection of dangerous fall events and the recognition of four main human postures (lie, sit, stand, bend) in Ambient Assisted Living applications. The suggested vision system uses a Time-Of-Flight camera providing accurate 3D measurements of the scene in all illumination conditions. In order to accommodate different installation setups, the system recovers automatically the own 3D position and orientation in the space, according to a floor detection strategy, without human intervention and calibration tools (landmarks, patterns, etc.). The moving people are detected in the 3D points cloud by applying segmentation/tracking methods and metric filtering. The distance of the 3D human centroid from the floor plane is evaluated by using the previously estimated calibration parameters and the corresponding trend is used as feature in a thresholding-based clustering for fall detection. The system shows high performances in terms of efficiency and reliability on a large real dataset of falls acquired in different conditions. The posture recognition is carried out by using both the 3D human centroid distance from the floor plane and the orientation of the body torso estimated by applying a topological approach to the range images. Experimental results on synthetic data validate the soundness of the proposed posture recognition approach.

This paper presents a multi-sensor system for the detection of people falls in the home environment. Two kinds of devices are used: a MEMS wearable wireless accelerometer with onboard fall detection algorithms and a 3D Time-of-Flight camera. An embedded computing system receives the possible fall alarm data from the two sub-sensory systems and their associated level of confidence. The computing module hosts a data fusion software to operate the validation and correlation among the two subsystems delivered data in order to rise overall system efficiency performance with respect to each single sensor sub-system.

In this work we characterised Negroamaro red wines, made by an autochthonous cultivar of Southern Italy, by linking volatile composition to aroma properties. This linking was carried out by picturing "Aroma Wheels", built by Odour Activity Values (OAVs) of all the identified volatile compounds grouped in "aromatic series" belonging to 13 classes of sensory descriptors. The 18 most active odorants with OAV>1 were mainly alcohols, fatty acids and their ethyl esters. The "OAVs' Aroma Wheels" showed that the classes of sensory descriptors are first fruity and floral, next fatty and pungent and minor nutty and caramelised notes. Principal Component Analysis displayed correlations between sensory descriptors and wine samples; the main 7-fruity and 5-floral sensory features of Negroamaro wines have negative values of PC1 and they are negatively correlated with the second main sensory feature, i.e. 13-fatty, falling at positive value of PC1; this fit the aroma perception of this varietal.

Wine aroma volatiles of two different typical Apulian wines made by autochthonous grape varieties (i.e. Negroamaro and Primitivo) were extracted by solid phase extraction (SPE) and analyzed using gas chromatography-mass spectrometry (GC-MS) in conjugation with an electronic nose (E-nose). Eighteen compounds were found over their own odour threshold and they were taken into account for further data analysis. Sensor data were analyzed by principal component analysis (PCA) to investigate the discrimination capability of the sensor array. The concentrations of volatile chemical compounds in wines determined by GC-MS have been correlated with electronic nose (E-nose) responses using partial least squares (PLSs) and quadratic response surface regression (RSR) analysis. By means of these regression models, relationships between E-nose responses and wine aroma compounds were established. Quite all of the 18 wine odorant concentration were predicted at a satisfactory extent; RSR technique gave better prediction results compared to PLS. © 2012 Elsevier B.V. All rights reserved.

Digital holography (DH) is a well-established interferometric tool in optical metrology allowing the investigation of engineered surface shapes with microscale lateral resolution and nanoscale axial precision. With the advent of charged coupled devices (CCDs) with smaller pixel sizes, high speed computers and greater pixel numbers, DH became a very feasible technology which offers new possibilities for a large variety of applications. DH presents numerous advantages such as the direct access to the phase information, numerical correction of optical aberrations and the ability of a numerical refocusing from a single hologram. Furthermore, as an interferometric method, DH offers both a nodestructive and no-contact approach to very fragile objects combined with flexibility and a high sensitivity to geometric quantities such as thicknesses and displacements. These features recommend it for the solution of many imaging and measurements problems, such as microelectro-optomechanical systems (MEMS/MEOMS) inspection and characterization. In this work, we propose to improve the performance of a DH measurement on MEMS devices, through digital filters. We have developed an automatic procedure, inserted in the hologram reconstruction process, to selectively filter the hologram spectrum. The purpose is to provide very few noisy reconstructed images, thus increasing the accuracy of the conveyed information and measures performed on images. Furthermore, improving the image quality, we aim to make this technique application as simple and as accurate as possible. © 2014 SPIE.

In this paper, shunt capacitive RF microelectromechanical systems (MEMS) switches are developed in III-V technology using tantalum nitride (TaN) and tantalum pentoxide (Ta2O5) for the actuation lines and the dielectric layers, respectively. A compositional, structural, and electrical characterization of the TaN and Ta2O5 films is preliminarily performed, demonstrating that they are valid alternatives to the conventional materials used in III-V technology for RF MEMS switches. Specifically, it is found that the TaN film resistivity can be tuned from 0.01 to 30 ohmcm . cm by changing the deposition parameters. On the other hand, dielectric Ta2O5 films show a low leakage-current density of few nanoamperes per square centimeter for E similar to 1 MV/cm, a high breakdown field of 4 MV/cm, and a high dielectric constant of 32. The realized switches show good actuation voltages, in the range of 15-20 V, an insertion loss better than -0.8 dB up to 30 GHz, and an isolation of similar to -40 dB at the resonant frequency, which is, according to bridge length, between 15 and 30 GHz. A comparison between the measured S-parameter values and the results of a circuit simulation is also presented and discussed, providing useful information on the operation of the fabricated switches.

TiO2 anatase nanocrystals were surface modified by deposition of V(V) species. The starting amorphous TiO2 nanoparticles were prepared by hydrolytic processing of TiCl4-derived solutions. A V-containing solution, prepared from methanolysis of VCl4, was added to the TiO2 suspension before a solvothermal crystallization step in oleic acid. The resulting materials were characterized by X-ray diffraction, transmission electron microscopy (TEM), Fourier transform infrared, Raman, and magic angle spinning solid-state V-51 nuclear magnetic resonance spectroscopy (MAS NMR). It was shown that in the as-prepared nanocrystals V was deposited onto the surface, forming Ti-O-V bonds. After heat treatment at 400 degrees C, TEM/electron energy loss spectroscopy and MAS NMR showed that V was partially inserted in the anatase lattice, while the surface was covered with a denser V-O-V network. After heating at 500 degrees C, V2O5 phase separation occurred, further evidenced by thermal analyses. The 400 degrees C nanocrystals had a mean size of about 5 nm, proving the successful synthesis of the colloidal counterpart of the well-known TiO2-V2O5 catalytic system. Hence, and also due to the complete elimination of organic residuals, this sample was used for processing chemoresistive devices. Ethanol was used as a test gas, and the results showed the beneficial effect of the V surface modification of anatase, with a response improvement up to almost 2 orders of magnitude with respect to pure TiO2. Moreover, simple comparison of the temperature dependence of the response clearly evidenced the catalytic effect of V addition.

The main goal of Ambient Assisted Living solutions is to provide assistive technologies and services in smart environments allowing elderly people to have high quality of life. Since 3D sensing technologies are increasingly investigated as monitoring solution able to outperform traditional approaches, in this work a noninvasive monitoring platform based on 3D sensors is presented providing a wide-range solution suitable in several assisted living scenarios. Detector nodes are managed by low-power embedded PCs in order to process 3D streams and extract postural features related to person's activities. The feature level of details is tuned in accordance with the current context in order to save bandwidth and computational resources. The platform architecture is conceived as a modular system suitable to be integrated into third-party middleware to provide monitoring functionalities in several scenarios. The event detection capabilities were validated by using both synthetic and real datasets collected in controlled and real-home environments. Results show the soundness of the presented solution to adapt to different application requirements, by correctly detecting events related to four relevant AAL services. © 2013 Alessandro Leone et al.

In recent years several world-wide ambient assisted living (AAL) programs have been activated in order to improve the quality of life of older people, and to strengthen the industrial base through the use of information and communication technologies. An important issue is extending the time that older people can live in their home environment, by increasing their autonomy and helping them to carry out activities of daily livings (ADLs). Research in the automatic detection of falls has received a lot of attention, with the object of enhancing safety, emergency response and independence of the elderly, at the same time comparing the social and economic costs related to fall accidents. In this work, an algorithmic framework to detect falls by using a 3D time-of-flight vision technology is presented. The proposed system presented complementary working requirements with respect to traditional worn and non-worn fall-detection devices. The vision system used a state-of-the-art 3D range camera for elderly movement measurement and detection of critical events, such as falls. The depth images provided by the active sensor allowed reliable segmentation and tracking of elderly movements, by using well-established imaging methods. Moreover, the range camera provided 3D metric information in all illumination conditions (even night vision), allowing the overcoming of some typical limitations of passive vision (shadows, camouflage, occlusions, brightness fluctuations, perspective ambiguity). A self-calibration algorithm guarantees different setup mountings of the range camera by non-technical users. A large dataset of simulated fall events and ADLs in real dwellings was collected and the proposed fall-detection system demonstrated high performance in terms of sensitivity and specificity. © 2011 IPEM.

We develop shunt capacitive RF MEMS switches in III-V technology making use of materials which can be alternative to the ones commonly used, in order to overcome some technological constraints concerning the RF MEMS reliability. Specifically, we evaluate the potential of tantalum nitride (TaN) and tantalum pentoxide (Ta2O5) to be used for the switches actuation pads and dielectric layers, respectively. To this scope, a compositional, structural and electrical characterization of TaN and Ta2O5 films as a function of the deposition parameters, such as the substrate temperature and the sputtering mixture composition, is performed. The realized switches show good actuation voltages, in the range 15- 20 V, an insertion loss better than -0.8 dB up to 30 GHz, and an isolation of ~ -40 dB at the resonant frequency. A comparison between the measured S-parameter values and the results of a circuit simulation is also presented and discussed, providing useful information on the operation of the fabricated switches.

The present research was motivated by the growing interest of the scientific community towards the understanding of basic gas-surface interaction mechanisms in 1D nanostructured metal oxide semiconductors, whose significantly enhanced chemical detection sensitivity is known. In this work, impedance spectroscopy (IS) was used to evaluate how a top-down patterning of the sensitive layer can modulate the electrical properties of a gas sensor based on a fully integrated nanometric array of TiO2 polycrystalline strips. The aim of the study was supported by comparative experimental activity carried out on different thin film gas sensors based on identical TiO2 polycrystalline sensitive thin films. The impedance responses of the investigated devices under dry air (as the reference environment) and ethanol vapors (as the target gas) were fitted by a complex nonlinear least-squares method using LEVM software, in order to find an appropriate equivalent circuit describing the main conduction processes involved in the gas/semiconductor interactions. Two different equivalent circuit models were identified as completely representative of the TiO2 thin film and the TiO2 nanostructure-based gas sensors, respectively. All the circuit parameters were quantified and the related standard deviations were evaluated. The simulated results well approximated the experimental data as indicated by the small mean errors of the fits (in the range of 10(-4)) and the small standard deviations of the circuit parameters. In addition to the substrate capacitance, three different contributions to the overall conduction mechanism were identified for both equivalent circuits: bulk conductivity, intergrain contact and semiconductor-electrode contact, electrically represented by an ideal resistor R-g, a parallel RgbCgb block and a parallel R-c-CPEc combination, respectively. In terms of equivalent circuit modeling, the sensitive layer patterning introduced an additional parameter in parallel connection with the whole circuit block. Such a circuit element (an ideal inductor, L) has an average value of about 125 mu H and exhibits no direct dependence on the analyte gas concentration. Its presence could be due to complex mutual inductance effects occurring both between all the adjacent nanostrips (10 mu m spaced) and between the nanostrips and the n-type-doped silicon substrate underneath the thermal oxide (wire/plate effect), where a two order of magnitude higher magnetic permeability of silicon can give L values comparable with those estimated by the fitting procedure. Slightly modified experimental models confirmed that the theoretical background, regulating thin film devices based on metal oxide semiconductors, is also valid for nanopatterned devices.

TiO2 and TiO2-V-2 O-5 nanocrystals were prepared by coupling sol-gel and solvothermal methods, followed by heat treatment at 400 degrees C, after which the nanocrystal mean size was still about 5 nm. The materials were used to process chemoresistive sensors, which were tested to ethanol and acetone, with concentrations ranging from 100 to 500 ppm and from 25 to 100 ppm, respectively. The sensing data evidenced that the surface deposition of V2O5 onto the anatase TiO2 nanocrystals enhanced the sensor response up to almost two orders of magnitude for both gases. Moreover, the sensors behavior was completely inverted: with TiO2-V2O5, the highest responses were obtained at the lowest operating temperatures, contrarily to pure TiO2, which required very high operating temperatures. The comparison of the sensing data allowed concluding that the V2O5 deposition effect could be interpreted as a catalytic contribution, in terms of lowered activation energies of the involved reactions and more favored gas adsorption at lower operating temperatures with respect to pure TiO2. (C) 2014 Elsevier B.V. All rights reserved.

Sn02 nanorods were successfully deposited on 3" Si/Si02 wafers by inductively coupled plasma-enhanced chemical vapor deposition (PECVD) and a wafer-level patterning of nanorods layer for miniaturized solid state gas sensor fabrication were performed. Uniform needle-shape Sn02 nanorods in situ grown were obtained under catalyst- and high temperature treatment-free growth condition. These nanorods have an average diameter between 5 and IS nm and a length of 160 to 300 nm. The Sn02-nanords based gas sensors were tested towards NH3 and CH30H and gas sensingtests show remarkable response, showing promising and repeatable results compared with the Sn02 thin films gas sensors.

SnO(2) nanorods were successfully deposited on 3" Si/SiO(2) wafers by inductively coupled plasma-enhanced chemical vapour deposition (PECVD) and a wafer-level patterning of nanorods layer for miniaturized solid state gas sensor fabrication were performed. Uniform needle-shaped SnO(2) nanorods in situ grown were obtained under catalyst- and high temperature treatment-free growth condition. These nanorods have an average diameter between 5 and 15 nm and a length of 160-300 nm. The SnO(2)-nanorods based gas sensors were tested towards NH(3) and CH(3)OH and gas sensing tests show remarkable response, showing promising and repeatable results compared with the SnO(2) thin films gas sensors.

Fe3O4/gamma-Fe2O3 nanoparticles (NPs) based thin films were used as active layers in solid state resistive chemical sensors. NPs were synthesized by high temperature solution phase reaction. Sensing NP monolayers (ML) were deposited by Langmuir-Blodgett (LB) techniques onto chemoresistive transduction platforms. The sensing ML were UV treated to remove NP insulating capping. Sensors surface was characterized by scanning electron microscopy (SEM). Systematic gas sensing tests in controlled atmosphere were carried out toward NO2, CO, and acetone at different concentrations and working temperatures of the sensing layers. The best sensing performance results were obtained for sensors with higher NPs coverage (10 ML), mainly for NO2 gas showing interesting selectivity toward nitrogen oxides. Electrical properties and conduction mechanisms are discussed.

In this work we proposed design, fabrication and functional characterization of a very low cost energy autonomous, maintenance free, flexible and wearable micro thermoelectric generator (mu TEG), finalized to power very low consumption electronics ambient assisted living (AAL) applications. The prototype. integrating an array of 100 thin films thermocouples of Sb(2)Te(3) and Bi(2)Te(3), generates, at 40 degrees C, an open circuit output voltage of 430 mV and an electrical output power up to 32 nW with matched load. In real operation conditions of prototype, which are believed to be very close to a thermal gradient of 15 degrees C. the device generates an open circuit output voltage of about 160 mV, with an electrical output power up to 4.18 nW.In the first part of work, deposition investigation Sb(2)T(e)3 and Bi(2)Te(3) thin films alloys on Kapton HN polyimide foil by RF magnetron co-sputtering technique is discussed. Deposition parameters have been optimized to gain perfect stoichiometric ratio and high thermoelectric power factor: fabricated thermo-generator has been tested at low gradient conditioned to evaluate applications like human skin wearable power generator for ambient assisted living applications.

WO3 precursor solutions were prepared by methanolysis of WCl6 in presence of acetylacetone as a stabilizer. Chromium addition was achieved by mixing Cr 2-ethylhexanoate with the pure solutions, with Cr: W atomic concentrations ranging from 2% to 22%. Powders were prepared by drying the solutions and heat-treating the product up to 700 degrees C. After heat-treating at 400 degrees C, crystalline WO3 was obtained, and X-ray diffraction and Transmission Electron Microscopy showed that the powders were constituted by a mixture of the WO3 monoclinic and triclinic crystallographic phases. The Cr-modified samples, with a Cr concentration of at least 5%, presented the additional phase Cr2WO6. Structural investigations suggested that this phase was favored instead of chromium oxides due to the incorporation of Cr in the WO3 lattice in interstitial position. The sensing tests towards ammonia gas, in concentrations ranging from 50 to 500 ppm, showed that, up to 5% concentration, Cr addition is beneficial in lowering the best operating temperatures and/or improving the response with respect to the pure powders. For higher Cr concentrations, the response severely decays. This result was interpreted in terms of the Cr2WO6 grains and of the influence of lowered concentration of interstitial Cr on the oxygen vacancies.

Breathanalysishasapowerfulpotentialfordiseasediagnosticsandmetabolicstatusmonitoring.Asol-gelSnOz­basedmicromachinedsensorarraywasdevelopedandtestedforpotentialapplicationinbreathanalysis.Asuitablebreathsamplingsystemwasusedtosamplethealveolarairvolumefromtheairvolumeofoneexpiration.Breathtestsonalveolarairsampledbysomevolunteers,i.e.smokersandnonsmokersindividuals,werecarried out.PrincipalComponentAnalysisappliedtogassensorresponsesshowedgoodpropertiesofdiscriminationbetweensmokersandnonsmokersindividuals.

In this paper an algorithmic framework for posture analysis using a single view 3D TOF camera is presented. The 3D human posture parameters are recovered automatically from range data without the usage of body markers. A topological approach is investigated in order to define descriptors suitable to estimate location of body parts and orientation of body articulations. Two Morse function are exploited, the first one provides an Euclidean distance mapping helpful to deal with body self-occlusions. The second Morse function is based on geodesic distance and provides an extended Discrete Reeb Graph description of the main body parts that are head, torso, arms and legs. Geodesic distance function exhibits the property of invariance under isometric transformations that typically occur when the human body changes its posture. The geodesic map of the body is obtained with a two steps procedure. Firstly, a Delaunay meshing is carried out starting from the depth map provided by the 3D TOF camera; secondly, geodesic distances are computed applying Dijkstra algorithm to previously computed mesh. Moreover, a re-meshing method is proposed in order to deal with self-occlusion problem which occurs in the depth data when a human body is partially occluded by other body segments. Experimental results on both synthetic and real data validate the effectiveness of the proposed approach to classifying four main postures: standing, lying, sitting and bending. © 2011 IEEE.

This paper presents a heterogeneous sensor platform for the detection of anomalies in circadian rhythm. Three detectors with different sensing principles are considered: a 3D time-of-flight camera, a MEMS wearable wireless accelerometer and a Ultra-wideband radar. Starting from human postural information obtained by each detector, a simulator of activities and related postures has been designed and implemented within this work. The use of a simulator is motivated by the lack of datasets containing long-term data for the analyzed context. The simulator is able to generate posture sequences calibrated on real experiments performed by each detector involved in the platform. Finally, a reasoner layer infers knowledge by using a suitable activity recognition module. Moreover, with an unsupervised clustering technique, the reasoner is able to detect specific circadian anomalies, thereby providing a tool for clinical evaluations. Experimental evaluation shows the effectiveness of the implemented solution, especially analyzing the performances related to the detection of anomalies varying sensing technology.

A non-invasive system for human posture recognition suitable to be used in several in-home scenarios is proposed and validation results presented. 3D point cloud sequences were acquired by using a time-of-flight sensor in a privacy preserving modality and near real-time processed with a low power embedded PC. To satisfy different application requirements in terms of discrimination capabilities, covered distance range and processing speed, a twofold discrimination approach was investigated in which features were hierarchical arranged from coarse to fine exploiting both topological and volumetric spatial representations. The topological representation encoded the intrinsic topology of the body's shape in a skeleton-based structure, guarantying invariance to scale, rotations and postural changes, and achieving a high level of detail with a moderate computational cost. In the volumetric representation, on the other hand, postures were described in terms of 3D cylindrical histograms working within a wider range of distances in a faster way and also guarantying good invariance properties. The discrimination capabilities of the approach were evaluated in four different real-home scenarios especially related with ambient assisted living and homecare fields, namely dangerous event detection, anomalous behavior detection, activities recognition, natural human-ambient interaction, and also in terms of invariance to viewpoint changes, representation capabilities and classification performance, achieving promising results. The two approaches exhibited complementary characteristics showing high reliability with classification rates greater than 97% in four application scenarios for which the posture recognition is a fundamental function. © 2012 Elsevier Ltd. All rights reserved.

In this work, the bridge imaging and the reliability of surface-micromachined capacitive RF MEMS switches in III-V technology are presented. A low cost scanning technique allowed us to image the shape of the moveable bridge with a micrometer spatial resolution, thus quantitatively valuating its lowering as a function of the applied voltage. The reliability of the switches was tested under the application of different unipolar and bipolar voltage waveforms, showing that a significant improvement of the switch operation and lifetime can be achieved by applying high frequency bipolar square pulses with suitable durations. © 2013 CMP.

Digital holographic microscopy is an important interferometric tool in optical metrology allowing the investigation of engineered surfaces with microscale lateral resolution and nanoscale axial precision. In particular, microelectromechanical systems (MEMS) surface analysis, conducted by holographic characterization, requires high accuracy for functional testing. The main issues related to MEMS inspection are the superficial roughness and the complex geometry resulting from the several fabrication steps. Here, an automatic procedure, particularly suited in the case of high-roughness surfaces, is presented to selectively filter the spectrum, providing very low-noise reconstructed images. The numerical procedure is based on Butterworth filtering, and the obtained results demonstrate a significant increase in the images' quality and in the accuracy of the measurements, making our technique highly applicable for quantitative phase imaging in MEMS analysis. Furthermore, our method is fully tunable to the spectrum under investigation and automatic. This makes it highly suitable for real-time applications. Several experimental tests show the suitability of the proposed approach. (C) 2015 Optical Society of America

Shunt capacitive radio-frequency microelectromechanical system (RF MEMS) switches were fabricated on silicon substrate and characterized in the RF domain. Various switch typologies were obtained by three different approaches, which are: (1) the change of the bridge geometric parameters, (2) the covering of the actuator with a floating metal, and (3) the deposition of the bridge directly on the actuator. The S parameters of the fabricated switches were measured in the up and down states, observing the impact on the RF performance of the variation of the geometric parameters and the fabrication process. The electromagnetic modelling of the fabricated switches was used to interpret the measured RF behaviour, allowing to elucidate the drawbacks of the non-perfect conforming of the bridge on the actuator. Finally, the reliability of the fabricated RF MEMS switches under a bipolar voltage excitation was evaluated by cycling tests. Hence, the study presented here provides guidelines to solve some issues of the tight correlation between design, fabrication, performance, and reliability of RF MEMS switches, in view of a large-scale development of these devices.

A non-invasive technique for posture classification suitable to be used in several in-home scenarios is proposed and preliminary validation results are presented. 3D point cloud sequences were acquired using a single time-of-flight sensor working in a privacy preserving modality and they were processed with a low power embedded PC. In order to satisfy different application requirements (e.g. covered distance range, processing speed and discrimination capabilities), a twofold discrimination approach was investigated in which features were hierarchically arranged from coarse to fine by exploiting both topological and volumetric representations. The topological representation encoded the intrinsic topology of the body's shape using a skeleton-based structure, thus guaranteeing invariance to scale, rotations and postural changes and achieving a high level of detail with a moderate computational cost. On the other hand, using the volumetric representation features were described in terms of 3D cylindrical histograms working within a wider range of distances in a faster way and also guaranteeing good invariance properties. The discrimination capabilities were evaluated in four different real-home scenarios related with the fields of ambient assisted living and homecare, namely "dangerous event detection", "anomalous behaviour detection", "activities recognition" and "natural human-ambient interaction". For each mentioned scenario, the discrimination capabilities were evaluated in terms of invariance to viewpoint changes, representation capabilities and classification performance, achieving promising results. The two feature representation approaches exhibited complementary characteristics showing high reliability with classification rates greater than 97%. © 2013 Elsevier B.V.

Shunt capacitive RF MEMS switches were developed on GaAs substrate, using a III-V technology process that is fully compatible with standard MMIC fabrication. The switches show an insertion loss lower than 0.8 dB and isolation better than 30 dB with resonance frequencies in K-band, according to the switch geometric parameters. Reliability limits due to dielectric charging were overcome by applying suitable fast bipolar actuation waveforms, making the developed switches good candidates for both redundancy (always on/off) and cycled applications.

Breath analysis, an innovative non-invasive diagnostic technique, bears the potential of drastically reducing the costs of medical diagnostics offering a simple alternative to standard blood analysis. Here, a flame spray pyrolysis (FSP) reactor was used for synthesis and direct deposition of nanostructured metal oxide (MOx) films onto microsensor substrates. These sensors were assembled in an array and tested simultaneously for different analytes requiring low power consumption to heat the sensor to the operating target temperature. The sensors had varying responses to the different analytes depending on sensing material (e.g. SnO2, WO3, ZnO), facilitating improvements on the selectivity of specific analytes (e.g. acetone, methanol, isoprene).

WO3 thin films were prepared by spin-coating methanol solutions of a tungsten chloromethoxide, and easily modified with Cr by the addition of Cr 2-ethylhexanoate. The films were heat-treated up to 700 degrees C, and characterized by X-ray diffraction, Scanning Electron Microscopy, Transmission Electron Microscopy and Electron Energy Loss spectroscopy. The film morphology was rough and porous, not depending on Cr presence, while their structure was constituted by packed spheroidal or elongated dense structures, giving rise to the peculiar film surface morphology. Cr was distributed in the film structure without phase separations, up to as high as 5% Cr atomic concentration.

The electrostatic actuation behaviour of the gold bridge in capacitive radio frequency microelectromechanical system switches, fabricated on GaAs substrate, is investigated. An unconventional imaging technique, based on the out-of-focus reflection, was used to evaluate the topographic profile of the suspended bridge and its lowering as a function of the voltage. Important parameters for the switch actuation, such as the pull-down voltage and the air gap between the bridge and the actuator, are estimated. Capacitance-voltage curves allow to evaluate the capacitance associated to the bridge in the up and down states as well as the dielectric constant of the Si<inf>3</inf>N<inf>4</inf> layer, which covers the actuator. The experimental values of the pull-down voltage and the dielectric constant are used to extract from the theoretical equations the residual stress of the fabricated gold membrane. Finally, the current through the dielectric Si<inf>3</inf>N<inf>4</inf> layer was measured as a function of the voltage applied to the actuator, finding that the Poole-Frenkel effect is the dominant conduction mechanism when the switch is actuated.

This paper presents an open platform for continuous monitoring of clinical signs through a smart and noninvasive wearable device. In order to accomplish a communication in proximity, the Near Field Communication wireless technology is used, providing a fast link between the device and the host, avoiding the pairing (as typically occurs for Bluetooth protocol) and limiting the power consumption. The Arduino ecosystem has been used for prototyping since it allows an easy and open integration of ad-hoc functionalities. The first prototype of the platform has been customized for human body temperature measurement, assuring a lifetime of the battery for at least 2 months. Moreover, the acquisition and related transmission of other kind of clinical signs could be easily implemented, making the platform cost-effective in mobile scenarios.

The present work highlights the progress in the field of polymeric package reliability engineering for a flexible thermoelectric generator realized by thin-film technology on a Kapton substrate. The effects of different plasma treatments on the mechanical performance at the interface of a poly-(dimethylsiloxane) (PDMS)/Kapton assembly were investigated. To increase the package mechanical stability of the realized wearable power source, the Kapton surface wettability after plasma exposure was investigated by static contact-angle measurements using deionized water and PDMS as test liquids. In fact, the well-known weak adhesion between PDMS and Kapton can lead to a delamination of the package with an unrecoverable damage of the generator. The plasma effect on the adhesion performances was evaluated by the scratch-test method. The best result was obtained by performing a nitrogen plasma treatment at a radio-frequency power of 20 W and a gas flow of 20 sccm, with a measured critical load of 1.45 N, which is 2.6 times greater than the value measured on an untreated Kapton substrate and 1.9 times greater than the one measured using a commercial primer.

In this paper, a computational framework for occupancy detection and profiling based exclusively on depth data is presented. 3D depth sensors offer many advantages against traditional video cameras. Occupants' privacy can be assured more effectively because depth information is unsuitable to reveal the person's identity. Notable low-level computer vision tasks can be simplified, thus lightening the computational load. The presented framework is suitable for wall-mounting setups as well as for ceiling-mounting setups, and scales well with the number of people. To take full advantage of depth data and to accommodate specificities of crowded environments, several improvements to the standard computer vision pipeline are suggested. Firstly, the running Gaussian average background model is adapted to work with depth distances in crowded scenes. Secondly, the classical complete linkage agglomerative clustering is boosted by adding edge-based constraints specifically designed for people segmentation in depth data. Thirdly, to reliable discriminate people, specific depth-based features are defined to be used with a Real AdaBoost classifier. The preliminary results achieved by using two different depth sensors and synthetic data are very promising, outperforming existing approaches. Relevant applications for building energy management, such as occupancy profiling and construction of trajectories and density maps, have been also demonstrated.

The optimization of a sensor array for a concrete analytical task is usually concerned with choosing a set of sensors to provide the best classification. In this work, a method for the prediction of the quality of classification by evaluation of the uniqueness of the raw experimental data is proposed. The key feature of the method is the presentation of the response of array as a function of the responses of its sensors. The dispersion of those functions serves as quantitative measure of uniqueness of the experimental data for a given set of analytes.The efficiency of the approach has been successfully demonstrated using both simulated and experimental data obtained from the array of three mass-sensitive sensors. The best conformity of the classification efficiency in cluster analysis with results obtained in the framework of the proposed approach is observed in the case of Langmuir-type adsorption processes.

Present work proposed design, finite element tools simulation and prototype fabrication of a low cost energy autonomous, maintenance free, flexible and wearable micro thermoelectric generator (mu TEG), finalized to power very low consumption electronics Ambient Assisted Living (AAL) applications. The prototype, integrating an array of 100 thin films thermocouples of Sb2Te3 and Bi2Te3, generates, at 40 degrees C, an open circuit output voltage of 430 mV and an electrical output power up to 32 nW with matched load. In real operation conditions of prototype, which are believed to be very close to a thermal gradient of 15 degrees C, the device generates an open circuit output voltage of about 160 mV, with an electrical output power up to 4.18 nW. In this work we proposed design, thermal simulation and fabrication of a preliminary flexible and wearable micro thermoelectric generator (mu TEG), finalized to power very low consumption electronics for Ambient Assisted Living (AAL) applications. Presented simulations show the performances of different fabrication solution for the PDMS/Kapton packages, considering flat and sloped walls approach for thermal gradient enhancement.

TiO2 nanocrystals were prepared by solvothermal treatment in oleic acid at 250 degrees C of amorphous TiO2 nanoparticles. The latter were prepared by sol-gel processing in dodecylamine at 100 degrees C of starting solutions synthesized from TiCl4. For preparing Pt/TiO2 nanocomposites, with Pt/Ti nominal atomic ratio of 0.05, the required amount of Pt precursor was added to the amorphous TiO2 nanoparticles before heating at 250 degrees C. Control synthesis experiments, evaluated by X-ray diffraction and X-ray photoelectron spectroscopy showed Pt(acac)(2) as the best Pt precursor, and 250 degrees C as the optimum temperature for simultaneous TiO2 crystallization and efficient Pt nucleation. Transmission electron microscopy observations evidenced Pt nanocrystals dispersed in the surrounding TiO2 host, with a mean size of 4 nm. The TiO2 host was constituted of rod-shaped anatase nanocrystals. Comparison with pure TiO2 showed that the rod shape was favored by the presence of Pt species. As an example of application, the nanocomposites were used for preparing ethanol-sensing devices. The Pt addition remarkably improved the response with respect to pure TiO2 sensors, and electrical characterization of the sensors helped in establishing that the effect of Pt was due to spillover rather than electronic sensitization.

The chapter presents an automated monitoring system for the detection of dangerous events of elderly people (such as falls) in AAL applications. In order to provide a self-contained technology solution not requiring neither the environment rearrangement, nor the presence of specialized staff, nor a priori information about elderly characteristics/habitude, the focus is placed on the classification of human postures and the detection of related adverse events. The people is detected through a non-wearable device (a TOF camera), overcoming the limitations of the wearable approaches (accelerometers, gyroscopes, etc.) for human monitoring (the devices are prone to be incorrectly worn or forgotten). The system shows high performances in terms of efficiency and reliability on a large real dataset of falls acquired in different conditions. The posture recognition is carried out by using a topological approach on the 3D points cloud. Experimental results validate the soundness of the posture recognition scheme. © 2011 Springer Science+Business Media B.V.

In this paper, the reliability of shunt capacitive radiofrequency microelectromechanical systems switches developed onGaAs substrate using a III-V technology fabrication process,which is fully compatible with standard monolithic microwaveintegrated circuit fabrication, is investigated. A comprehensivecycling test is carried out under the application of different unipolarand bipolar polarization waveforms in order to infer howthe reliability of the realized capacitive switches, which is stilllimited with respect to the silicon-based devices due to the lessconsolidation of the III-V technology, can be improved. Underthe application of unipolar waveforms, the switches show a shortlifetime and a no correct deactuation for positive pulses longerthan ~10 ms probably due to the charging phenomena occurringin the dielectric layer underneath the moveable membrane. Thesecharging effects are found to vanish under the application ofa waveform including consecutive positive and negative voltagepulses, provided that proper durations of the positive and negativevoltage pulses are used. Specifically, a correct switch deactuationand a lifetime longer than 1 million cycles, being this value limitedby the duration of the used testing excitation, are achieved byapplying a 1-kHz waveform with 20-?s-long positive and negativeconsecutive pulses.

Ta2O5 thin films were prepared by spin-coating methanol solutions of Ta chloromethoxide. It was prepared by reacting TaCl5 with methanol, followed by water addition (H2O: Ta molar ratio was 16). Thin films were deposited by spin-coating onto SiO2/Si substrates, followed by drying at 90 degrees C and heat-treatment up to 700 degrees C. The films were characterized by X-ray diffraction, transmission electron microscopy and field emission scanning electron microscopy. Crystallization was obtained only after heating at 700 degrees C, in the Ta2O5 orthorhombic phase. The resulting films had a thickness of 100 nm. Their structure was constituted by porous crystals with size up to 50 nm, while the pores had a size of about 10 nm. The results demonstrated that TaCl5 is very convenient precursor for the wet chemical synthesis of Ta2O5 thin films. (C) 2013 Elsevier B.V. All rights reserved.

We report for the first time the synthesis of monoclinic WO3 quantum dots. A solvothermal processing at 250 degrees C in oleic acid of W chloroalkoxide solutions was employed. It was shown that the bulk monoclinic crystallographic phase is the stable one even for the nanosized regime (mean size 4 nm). The nanocrystals were characterized by X-ray diffraction, High resolution transmission electron microscopy, X-ray photoelectron spectroscopy, UV-vis, Fourier transform infrared and Raman spectroscopy. It was concluded that they were constituted by a core of monoclinic WO3, surface covered by unstable W(V) species, slowly oxidized upon standing in room conditions. The WO3 nanocrystals could be easily processed to prepare gas-sensing devices, without any phase transition up to at least 500 degrees C. The devices displayed remarkable response to both oxidizing (nitrogen dioxide) and reducing (ethanol) gases in concentrations ranging from 1 to 5 ppm and from 100 to 500 ppm, at low operating temperatures of 100 and 200 degrees C, respectively. The analysis of the electrical data showed that the nanocrystals were characterized by reduced surfaces, which enhanced both nitrogen dioxide adsorption and oxygen ionosorption, the latter resulting in enhanced ethanol decomposition kinetics.

The objective of this paper is to study the morphology, structure, and composition, as well as the thermal-induced morphological, structural, and chemical changes of copper(Cu)/titanium nitride(TiN) bilayers versus Cu single layers, deposited on silicon substrates for microelectronic applications. These characterizations aimed to assess the reliability of Cu metallization for local interconnect and to investigate the barrier capability of TiN against Cu diffusion into the silicon (Si) substrate. Moreover, this paper provides a fundamental study of the temperature-induced interactions between Cu and Si, intermediated by the presence of a thin TiN layer. Cu thin films were sputtered onto Si substrates, with and without the interposition of thin TiN layers, and were successively annealed at temperature as high as 600. C. Different nitrogen flux percentages in the sputtering mixture (Ar + N-2) were used for the deposition of the barriers. X-ray diffraction (XRD) analyses were carried out in order to study the structural evolution of the layers, before and after the annealing. Scanning electron microscopy (SEM) observations gave information about the surface and cross section morphology, and spatially resolved energy dispersive X-ray Spectroscopy (EDS) profiles provided chemical information about the cross-sectional distribution of the atomic species and their possible interdiffusion. The barrier efficacy has been demonstrated by comparing the morphological and chemical modifications of the annealed Cu layers, with and without the presence of the TiN layer, and their effects on the electrical properties of the Cu films.

Falling is one of the main causes of trauma, disability, and death among older people. Inertial sensors-based devices are able to detect falls in controlled environments. Often this kind of solution presents poor performances in real conditions. The aim of this work is the development of a computationally low-cost algorithm for feature extraction and the implementation of a machine-learning scheme for people fall detection, by using a triaxial MEMS wearable wireless accelerometer. The proposed approach allows to generalize the detection of fall events in several practical conditions. It appears invariant to the age, weight, height of people, and to the relative positioning area (even in the upper part of the waist), overcoming the drawbacks of well-known threshold-based approaches in which several parameters need to be manually estimated according to the specific features of the end user. In order to limit the workload, the specific study on posture analysis has been avoided, and a polynomial kernel function is used while maintaining high performances in terms of specificity and sensitivity. The supervised clustering step is achieved by implementing an one-class support vector machine classifier in a stand-alone PC. © 2013 Gabriele Rescio et al.

Fall events can cause trauma, disability and death among older people. Accelerometer-based devices are able to detect falls in controlled environments. The paper presents a computationally low-power approach for feature extraction and supervised clustering for people fall detection by using a 3-axial MEMS wearable accelerometer, managed by an stand-alone PC through ZigBee connection. The paper extends a previous work in which fall events were detected according to a threshold-based scheme. The proposed approach allows to generalize the detection of falls in several practical conditions, after a short period of calibration. The clustering scheme appears invariant to age, weight, height of people and relative positioning area (even in the upper part of the waist), overcoming the drawbacks of well-known threshold-based approaches in which several parameters need to be manually estimated, according to the specific features of the end-user. In order to limit the workload, the specific study on posture analysis has been avoided and a polynomial kernel function is used while maintaining high performance in terms of specificity and sensitivity. The supervised clustering step is achieved by implementing an One- Class Support Vector Machine classifier. © 2013 IEEE.

Falling down events can cause trauma, disability and death among older people. Accelerometer-based devices are able to detect falls in controlled environments. This kind of solution often presents poor performance in real conditions. The aim of this work is the development of a computationally low-cost algorithm for feature extraction and the implementation of a Machine Learning scheme for people fall detection, by using a tri-axial MEMS wearable wireless accelerometer. The proposed approach allows to generalize the detection of fall events in several practical conditions. It appears invariant to the age, weight, height of people and to the relative positioning area (even in the upper part of the waist), overcoming the drawbacks of well-known threshold-based approaches in which several parameters need to be manually estimated according to the specific features of the end-user. In order to limit the workload, the specific study on posture analysis has been avoided and a polynomial kernel function is used while maintaining high performance in terms of specificity and sensitivity. The supervised clustering step is achieved by implementing an One-Class Support Vector Machine classifier in a stand-alone PC. © 2013 IEEE.

The aim of this work is the development of a computationally low-cost scheme for feature extraction and the implementation of an One-class Support Vector Machine classifier for people fall detection, by using a tri-axial MEMS wearable wireless accelerometer, managed by a stand-alone PC through ZigBee connection. The proposed approach allows the generalization of the detection of fall events in several practical conditions after a short period of calibration. The approach appears invariant to age, weight, people's height and the relative positioning area (even in the upper part of the waist) This overcomes the drawbacks of well-known threshold-based approaches in which several parameters need to be manually estimated according to the specific features of the end-user. In order to limit the workload, the specific study on posture analysis has been avoided and a polynomial kernel function is used, while maintaining high performances in terms of specificity and sensitivity. © 2013 IEEE.

WO3 and Cr-WO3 powders were prepared by sol-gel process, with Cr:W atomic concentration ranging from 2% to 8.8%. WCl6 was used as W precursor and reacted with methanol in presence of acetyacetone as stabilizer. The required amount of Cr 2-ethylhexanoate was then added to the resulting solution, which was subsequently dried. The resulting powder was heat-treated at temperatures ranging from 200 to 700 degrees C. With increasing the Cr concentration, the samples heat-treated at 500 degrees C contained an increasing amount of the additional phase Cr2WO6, as evidenced by X-ray diffraction and Transmission Electron Microscopy. The sensing tests toward ammonia gas, from 50 to 500 ppm showed that, up to 5% concentration, Cr addition lowered the best operating temperatures and/or enhanced the response with respect to pure WO3, then the response remarkably decayed. DFT modeling showed that Cr(III) incorporation was more favorable in interstitial position while Cr (VI) was more favored in substitutional configuration. In this case, highly acidic Cr sites are present, enhancing the adsorption of ammonia species and reactions not involving NO2 as by-product. Beyond 5% Cr concentration, Cr2WO6 formation extracts Cr from the WO3 structure, so decreasing the ammonia response. Moreover, the appearance of Cr2WO6 seems to deactivate the surface adsorption properties of the material.

In this work, single walled carbon nanotubes (SWNTs) have been chemically functionalized at their walls with a membrane protein, namely the mutated bacteriorhodopsin D96N, integrated in its native archaeal lipid membrane. The modification of the SWNT walls with the mutant has been carried out in different buffer solutions, at pH 5, 7.5 and 9, to investigate the anchoring process, the typical chemical and physical properties of the component materials being dependent on the pH. The SWNTs modified by interactions with bacteriorhodopsin membrane patches have been characterized by UV-vis steady state, Raman and attenuated total reflection Fourier transform infrared spectroscopy and by atomic force and transmission electron microscopy. The investigation shows that the membrane protein patches wrap the carbon walls by tight chemical interactions undergoing a conformational change; such chemical interactions increase the mechanical strength of the SWNTs and promote charge transfers which p-dope the nano-objects. The functionalization, as well as the SWNT doping, is favoured in acid and basic buffer conditions; such buffers make the nanotube walls more reactive, thus catalysing the anchoring of the membrane protein. The direct electron communication among the materials can be exploited for effectively interfacing the transport properties of carbon nanotubes with both molecular recognition capability and photoactivity of the cell membrane for sensing and photoconversion applications upon integration of the achieved hybrid materials in sensors or photovoltaic devices.

TiO2 anatase nanocrystals were prepared by solvothermal processing of Ti chloroalkoxide in oleic acid, in the presence of W chloroalkoxide, with W/Ti nominal atomic concentration (R-w) ranging from 0.16 to 0.64. The as-prepared materials were heat-treated up to 500 degrees C for thermal stabilization and sensing device processing. For R0.16, the as-prepared materials were constituted by an anatase core surface-modified by WOx monolayers. This structure persisted up to 500 degrees C, without any WO3 phase segregation. For Rw up to R0.64, the anatase core was initially wrapped by an amorphous WOx gel. Upon heat treatment, the WOx phase underwent structural reorganization, remaining amorphous up to 400 degrees C and forming tiny WO3 nanocrystals dispersed into the TiO2 host after heating at 500 degrees C, when part of tungsten also migrated into the TiO2 structure, resulting in structural and electrical modification of the anatase host. The ethanol sensing properties of the various materials were tested and compared with pure TiO2 and WO3 analogously prepared. They showed that even the simple surface modification of the TiO2 host resulted in a 3 orders of magnitude response improvement with respect to pure TiO2.

The modification of the surface reception properties of nanocrystalline structures is of great interest in environmental, catalysis and energy related applications. For instance, an oxide surface covered with a layer of another oxide opens the possibility of creating the nanosized counterparts of bulk catalytic systems. A relevant example is the TiO2-WO3, which is an active catalysts in a broad range of reactions. The chemical synthesis of the colloidal, nanocrystalline version of such system will first be exposed, by coupling suitable sol-gel chemistry with solvothermal processing. Then, the range of obtained structures will be discussed, ranging from WOx-surface modified TiO2 to TiO2-WO3 heterojunctions. The complex structural evolution of the materials will be discussed, depending on the W concentration. A summary of the acetone sensing properties of these systems will be shown. In particular, the surface activation of the otherwise almost inactive pure TiO2 by surface deposition of WO3-like layers will be highlighted. Addition of the smallest W concentration boosted the sensor response to values comparable to those of pure WO3, ranging over 2-3 orders of magnitude of conductance variation in presence of ethanol or acetone gases. Simple analysis of the sensing data will evidence that the combination of such nanocrystalline oxides results in catalytic activation effects, with exactly opposite trend, with respect to pure TiO2, of the activation energies and best responses.

ZnO nanocrystals (2.5-4.5 nm) were prepared by a wet chemical method based on alkaline-activated hydrolysis and condensation of zinc acetate solutions. Dropcasting of the nanocrystals onto alumina substrates allowed the fabrication of gas sensing devices, that were tested towards NO2, acetone and methanol and showed promising results. At low working temperature, the ZnO quantum dots based sensors are selective to nitrogen oxide, in fact a good sensitivity is shown at 200 degrees C at low concentration (2 ppm), while at temperature above 350 degrees C, high responses are obtained for acetone and methanol. The results obtained are stimulating for further developing of nano-ZnO based sensor devices.

Shunt capacitive RF MEMS switches have been developed using III-V technology and employing (tantalum pentoxide) Ta2O5 thin films as dielectric layers. In order to evaluate the potential of the Ta2O5 thin films for the considered application, the compositional, structural, and electrical characterization of the deposited films has been performed, demonstrating that they are good candidates to be used as dielectric layers for the fabrication of RF MEMS switches. Specifically, Ta2O5 films are found to show a leakage current density of few nA/cm2 for MV/cm and a high dielectric constant of 32. Moreover, the charging process has been investigated, finding that it follows a stretched exponential law. The fabricated switches show actuation voltages in the range 15-20 V, an insertion loss better than -0.8 dB up to 30 GHz, and an isolation of ~-40 dB at the resonant frequency which is around 25 GHz.

Shunt capacitive radio-frequency microelectromechanical (RF MEMS) switches were modelled, fabricated and characterized in the K-band domain. Design allowed to predict the RF behaviour of the switches as a function of the bridge geometric parameters. The modelled switches were fabricated on silicon substrate, using a surface micromachining approach. In addition to the geometric parameters, the material structure in the bridge-actuator area was modified for switches fabricated on the same wafer, thanks to the removal/addition of two technological steps of crucial importance for RF MEMS switches performance, which are the use of the sacrificial layer and the deposition of a floating metal layer on the actuator. Surface profilometry analysis was used to check the material layer structure in the different regions of the bridge area as well as to investigate the mechanical behaviour of the moveable bridge under the application of a loaded force. The RF behaviour of all the fabricated switches was measured, observing the impact on the isolation of the manipulation of the bridge size and of the variations in the fabrication process.

TiO2 and TiO2-V2O5 nanocrystals were prepared by coupling sol-gel and solvothermal methods, followed by heat-treatment at 400 degrees C, after which the mean nanocrystal size was about 5 nm. The materials were characterized by X-ray diffraction, transmission electron microscopy and solid state nuclear magnetic resonance spectroscopy. It was shown that while the TiO2 phase was always anatase even after heat-treatment at 500 degrees C, the presence of the vanadium oxide species enhanced the surface re-configuration of the Ti ions. Hence the coordination environment of surface Ti atoms was drastically changed, by formation of further bonds and imposition of a given local geometry. The final hypothesis was that in pure titania surface rearrangement occurs, leading to the new NMR signal, but this modification was favored in the TiO2-V2O5 sample, where the Ti surface atoms were forced into the final configurations by the bonding with V atoms through oxygen. The materials heat-treated at 400 degrees C were used to process chemoresistive sensors, which were tested to hydrogen, CO and NO2, as examples of gases with peculiar sensing mechanisms. The results evidenced that the surface deposition of V2O5 onto the anatase TiO2 nanocrystals was effective in modifying the adsorption properties of the anatase nanocrystals. (C) 2015 Elsevier B.V. All rights reserved.

The main goal of Ambient Assisted Living solutions is to provide assistive technologies and services in smart environments allowing to elderly people to have high quality of life. Since Time-Of-Flight vision technologies are increasingly investigated as monitoring solution able to outperform traditional approaches, in this work a monitoring framework based on a Time-Of-Flight sensor network has been investigated with the aim to provide a wide-range solution suitable in several assisted living scenarios. Detector nodes are managed by a low-power embedded PC to process Time-Of-Flight streams and cxtract features related with person's activities. The feature level of detail is tuned in an application-driven manner in order to optimize both bandwidth and computational resources. The event detection capabilities were validated by using data collected in real-home environments. © 2013 The Authors. Published by Elsevier B.V.

The paper presents an active vision system for human posture recognition, which is an important function of any assisted living system, suitable to be employed in indoor environments. Both hardware and software architectures are defined in order to meet constraints typically imposed by AAL (Ambient Assisted Living) contexts such as compactness, low-power consumption, installation simplicity, privacy preserving and non-intrusiveness. Two different approaches for feature extraction (topological and volumetric) are discussed and the related discrimination capabilities evaluated by using a statistical learning methodology. Experimental results show the soundness of the presented active vision-based solution in order to classify four main human postures (standing, sitting, bent, lying) with an adequate detail level for the specific AAL application. © 2011 IEEE.

The potential of sputtered Ta2O5 thin films to be used as dielectric layers in capacitive radio frequency microelectromechanical system switches is evaluated by investigating two factors of crucial importance for the performance of these devices which are the transport mechanisms and the charging effects in the dielectric layer. We find that Ta2O5 films show good electrical and dielectrical properties for the considered application in terms of a low leakage current density of 4 nA/cm(2) for E=1 MV/cm, a high breakdown field of 4 MV/cm and a high dielectric constant of 32. For electric fields lower than 1 MV/cm the conduction mechanism is found to be variable-range hopping in the temperature range 300-400 K, while nearest-neighbor hopping is observed at higher temperatures. For fields in the range 1-4 MV/cm Poole-Frenkel becomes the dominant conduction mechanism. Current and capacitance transients used to investigate the charging effects show a decay which is well described by the stretched-exponential law, thus providing further insights on capture and emission processes.

A titanium chloromethoxide solution was prepared by reacting TiCl(4) with methanol, followed by water addition. The starting solutions were characterized by Fourier Transform Infrared (FTIR) spectroscopy, evidencing that the in situ generated water results in early hydrolysis of the chloroalkoxide. The solution was reacted with molten dodecylamine at room temperature, obtaining a white slurry of amorphous titania nanoparticles. Stable, redispersible TiO(2) nanocrystals could be prepared by subsequent solvothermal treatment in oleic acid at 250 A degrees C. The use of oleic acid was essential for obtaining crystalline structures, while other surfactants prevented crystallization. The nanocrystals were characterized by X-ray Diffraction and Transmission Electron Microscopy, confirming the formation of anatase TiO(2) nanocrystals with a mean size of 3.3 nm. The TiO(2) nanocrystals were used for fabricating gas-sensing devices, which were tested towards ethanol vapors. The initial small size of the nanocrystals, and the limited size growth during the high-temperature sensor operation, result in remarkable sensing performances if compared with bulk titania sensors.

Volatile composition of monovarietal young red wines made from Negroamaro cultivar, an autochthonous grape variety of Vitis vinifera grown exclusively in Solento area (southeast of Italy in Apulia region), was investigated. Volatile compounds were extracted following a solid phase extraction (SPE) method, and then analysed by gas chromatography-mass spectrometry (GC/MS). Results showed a complex aroma profile rich in alcohols, esters and fatty acids, with a minor contribute from aldehydes, lactones, volatile phenols and sulphur compounds. For the first time, aromatic patterns that characterise wines produced from Negroamaro autochthonous grape variety were established, starting a fundamental register of typicity and geographical identity of Apulians wines. Statistical data analysis techniques (Principal component analysis (PCA) and ANOVA) showed the structure of the experimental data and the significant differences for each compound in the different wines. (C) 2011 Elsevier Ltd. All rights reserved.

Volatile metabolites from mold contamination have been proposed for the early identification of toxigenic fungi to prevent toxicological risks, but there are no such data available for Fusarium poae. F. poae is one of the species complexes involved in Fusarium head blight, a cereal disease that results in significant yield losses and quality reductions. The identification of volatile organic compounds associated with F. poae metabolism could provide good markers to indicate early fungal contamination. To this aim, we evaluated the volatile profile of healthy and F. poae-infected durum wheat kernels by SPME-GC/MS analysis. The production of volatile metabolites was monitored for seven days, and the time course analysis of key volatiles was determined. A total of 29 volatile markers were selected among the detected compounds, and multivariate analysis was applied to establish the relationship between potential volatile markers and fungal contamination. A range of volatile compounds, including alcohols, ketones, esters, furans and aromatics, were identified, both in contaminated and in healthy kernels. However, the overall volatile profile of infected samples and controls differed, indicating that the whole volatile profile, rather than individual volatile compounds, could be used to identify F. poae contamination of durum wheat grains.