920 resultados para Ultrasound sensors


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A novel method for obtaining information on the charge density of an immersed surface is presented. The technique uses focused ultrasound to excite oscillatory fluid motion in the plane of the solid-liquid interface, over a localised area. The displacement current (resulting from the motion of fluid-borne ions in the outer double-layer) is detected by electrodes in the liquid. The method is demonstrated as a means for monitoring protein adsorption, and for monitoring interactions between two different proteins. A second electrokinetic effect at the interface is identified, isolated from the first, and shown to provide additional information on the compressibility and charge density of the double-layer. © 2001 Elsevier Science B.V. All rights reserved.

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Optical sensors for ultrasound detection provide high sensitivity and bandwidth, essential for photoacoustic imaging in clinical diagnostics and biomedical research. Implementing plasmonic metamaterials in a non-resonant regime facilitates sub-nanosecond, highly sensitive detectors while eliminating cumbersome optical alignment necessary for resonant sensors.

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Rats are superior to the most advanced robots when it comes to creating and exploiting spatial representations. A wild rat can have a foraging range of hundreds of meters, possibly kilometers, and yet the rodent can unerringly return to its home after each foraging mission, and return to profitable foraging locations at a later date (Davis, et al., 1948). The rat runs through undergrowth and pipes with few distal landmarks, along paths where the visual, textural, and olfactory appearance constantly change (Hardy and Taylor, 1980; Recht, 1988). Despite these challenges the rat builds, maintains, and exploits internal representations of large areas of the real world throughout its two to three year lifetime. While algorithms exist that allow robots to build maps, the questions of how to maintain those maps and how to handle change in appearance over time remain open. The robotic approach to map building has been dominated by algorithms that optimise the geometry of the map based on measurements of distances to features. In a robotic approach, measurements of distance to features are taken with range-measuring devices such as laser range finders or ultrasound sensors, and in some cases estimates of depth from visual information. The features are incorporated into the map based on previous readings of other features in view and estimates of self-motion. The algorithms explicitly model the uncertainty in measurements of range and the measurement of self-motion, and use probability theory to find optimal solutions for the geometric configuration of the map features (Dissanayake, et al., 2001; Thrun and Leonard, 2008). Some of the results from the application of these algorithms have been impressive, ranging from three-dimensional maps of large urban strucutures (Thrun and Montemerlo, 2006) to natural environments (Montemerlo, et al., 2003).

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Mobile robots need autonomy to fulfill their tasks. Such autonomy is related whith their capacity to explorer and to recognize their navigation environments. In this context, the present work considers techniques for the classification and extraction of features from images, using artificial neural networks. This images are used in the mapping and localization system of LACE (Automation and Evolutive Computing Laboratory) mobile robot. In this direction, the robot uses a sensorial system composed by ultrasound sensors and a catadioptric vision system equipped with a camera and a conical mirror. The mapping system is composed of three modules; two of them will be presented in this paper: the classifier and the characterizer modules. Results of these modules simulations are presented in this paper.

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Autonomous robots must be able to learn and maintain models of their environments. In this context, the present work considers techniques for the classification and extraction of features from images in joined with artificial neural networks in order to use them in the system of mapping and localization of the mobile robot of Laboratory of Automation and Evolutive Computer (LACE). To do this, the robot uses a sensorial system composed for ultrasound sensors and a catadioptric vision system formed by a camera and a conical mirror. The mapping system is composed by three modules. Two of them will be presented in this paper: the classifier and the characterizer module. The first module uses a hierarchical neural network to do the classification; the second uses techiniques of extraction of attributes of images and recognition of invariant patterns extracted from the places images set. The neural network of the classifier module is structured in two layers, reason and intuition, and is trained to classify each place explored for the robot amongst four predefine classes. The final result of the exploration is the construction of a topological map of the explored environment. Results gotten through the simulation of the both modules of the mapping system will be presented in this paper. © 2008 IEEE.

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Various leg exercises have been recommended to prevent deep vein thrombosis (DVT), a condition where a blood clot forms in the deep veins, especially during long-haul flights. Accessing the benefit of each of these exercises in avoiding the DVT, which can be fatal, is important in the context of suggesting the correct and the most beneficial exercises. Present work aims at demonstrating the fiber Bragg grating (FBG)-based sensing methodology for measuring surface strains generated on the skin of the calf muscle to evaluate the suggested airline exercises to avoid DVT. As the dataset in the experiment involves multiple subjects performing these exercises, an inertial measurement unit has been used to validate the repetitiveness of each of the exercises. The surface strain on the calf muscle obtained using the FBG sensor, which is a measure of the calf muscle deformation, has been compared against the variation of blood velocity in the femoral vein of the thigh measured using a commercial electronic-phased array color Doppler ultrasound system. Apart from analyzing the effectiveness of suggested exercises, a new exercise which is more effective in terms of strain generated to avoid DVT is proposed and evaluated. (C) 2013 Society of Photo-Optical Instrumentation Engineers (SPIE)

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We report a characterization of the acoustic sensitivity of microstructured polymer optical fiber interferometric sensors at ultrasonic frequencies from 100kHz to 10MHz. The use of wide-band ultrasonic fiber optic sensors in biomedical ultrasonic and optoacoustic applications is an open alternative to conventional piezoelectric transducers. These kind of sensors, made of biocompatible polymers, are good candidates for the sensing element in an optoacoustic endoscope because of its high sensitivity, its shape and its non-brittle and non-electric nature. The acoustic sensitivity of the intrinsic fiber optic interferometric sensors depends strongly of the material which is composed of. In this work we compare experimentally the intrinsic ultrasonic sensitivities of a PMMA mPOF with other three optical fibers: a singlemode silica optical fiber, a single-mode polymer optical fiber and a multimode graded-index perfluorinated polymer optical fiber. © 2014 SPIE.

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Opto-Acoustic Endoscopy (OAE) requires sensors with a high sensitivity and small physical dimensions in order to facilitate integration into an endoscope of less than 1mm in diameter. We present fibre Bragg grating (FBG) and Fabry- Perot intrinsic fibre sensors for ultrasound detection. We present a structure profile characterisation setup to analyse tune the fibre sensors in preparation for ultrasonic detection. We evaluate the suitability of the different structures and grating parameters for ultrasonic sensing. By analysing the prepared gratings, we enable the optimisation of the profile and a simplification of the detection regime for an optimal interferometric OAE configuration.

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Opto-acoustic imaging (OAI) shows particular promise for in-vivo biomedical diagnostics. Its applications include cardiovascular, gastrointestinal and urogenital systems imaging. Opto-acoustic endoscopy (OAE) allows the imaging of body parts through cavities permitting entry. The critical parameter is the physical size of the device, allowing compatibility with current technology, while governing flexibility of the distal end of the endoscope based on the needs of the sensor. Polymer optical fibre (POF) presents a novel approach for endoscopic applications and has been positively discussed and compared in existing publications. A great advantage can be obtained for endoscopy due to a small size and array potential to provide discrete imaging speed improvements. Optical fibre exhibits numerous advantages over conventional piezo-electric transducers, such as immunity from electromagnetic interference and a higher resolution at small sizes. Furthermore, micro structured polymer optical fibres offer over 12 times the sensitivity of silica fibre. We present a polymer fibre Bragg grating ultrasound detector with a core diameter of 125 microns. We discuss the ultrasonic signals received and draw conclusions on the opportunities and challenges of applying this technology in biomedical applications.

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Polymer optical fibre (POF) is a relatively new and novel technology that presents an innovative approach for ultrasonic endoscopic applications. Currently, piezo electric transducers are the typical detectors of choice, albeit possessing a limited bandwidth due to their resonant nature and a sensitivity that decreases proportionally to their size. Optical fibres provide immunity from electromagnetic interference and POF in particular boasts more suitable physical characteristics than silica optical fibre. The most important of these are lower acoustic impedance, a reduced Young's Modulus and a higher acoustic sensitivity than single-mode silica fibre at both 1 MHz and 10 MHz. POF therefore offers an interesting alternative to existing technology. Intrinsic fibre structures such as Bragg gratings and Fabry-Perot cavities may be inscribed into the fibre core using UV lasers. These gratings are a modulation of the refractive index of the fibre core and provide the advantages of high reflectivity, customisable bandwidth and point detection. We present a compact in fibre ultrasonic point detector based upon a POF Bragg grating (POFBG) sensor. We demonstrate that the detector is capable of leaving a laboratory environment by using connectorised fibre sensors and make a case for endoscopic ultrasonic detection through use of a mounting structure that better mimics the environment of an endoscopic probe. We measure the effects of water immersion upon POFBGs and analyse the ultrasonic response for 1, 5 and 10 MHz.

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Opto-acoustic imaging is a growing field of research in recent years, providing functional imaging of physiological biomarkers, such as the oxygenation of haemoglobin. Piezo electric transducers are the industry standard detector for ultrasonics, but their limited bandwidth, susceptibility to electromagnetic interference and their inversely proportional sensitivity to size all affect the detector performance. Sensors based on polymer optical fibres (POF) are immune to electromagnetic interference, have lower acoustic impedance and a reduced Young's Modulus compared to silica fibres. Furthermore, POF enables the possibility of a wideband sensor and a size appropriate to endoscopy. Micro-structured POF (mPOF) used in an interferometric detector has been shown to be an order of magnitude more sensitive than silica fibre at 1 MHz and 3 times more sensitive at 10 MHz. We present the first opto-acoustic measurements obtained using a 4.7mm PMMA mPOF Bragg grating with a fibre diameter of 130 μm and present the lateral directivity pattern of a PMMA mPOF FBG ultrasound sensor over a frequency range of 1-50 MHz. We discuss the impact of the pattern with respect to the targeted application and draw conclusions on how to mitigate the problems encountered.