916 resultados para lumbar fusion
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Knowing exactly where a mobile entity is and monitoring its trajectory in real-time has recently attracted a lot of interests from both academia and industrial communities, due to the large number of applications it enables, nevertheless, it is nowadays one of the most challenging problems from scientific and technological standpoints. In this work we propose a tracking system based on the fusion of position estimations provided by different sources, that are combined together to get a final estimation that aims at providing improved accuracy with respect to those generated by each system individually. In particular, exploiting the availability of a Wireless Sensor Network as an infrastructure, a mobile entity equipped with an inertial system first gets the position estimation using both a Kalman Filter and a fully distributed positioning algorithm (the Enhanced Steepest Descent, we recently proposed), then combines the results using the Simple Convex Combination algorithm. Simulation results clearly show good performance in terms of the final accuracy achieved. Finally, the proposed technique is validated against real data taken from an inertial sensor provided by THALES ITALIA.
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The foot and the ankle are small structures commonly affected by disorders, and their complex anatomy represent significant diagnostic challenges. SPECT/CT Image fusion can provide missing anatomical and bone structure information to functional imaging, which is particularly useful to increase diagnosis certainty of bone pathology. However, due to SPECT acquisition duration, patient’s involuntary movements may lead to misalignment between SPECT and CT images. Patient motion can be reduced using a dedicated patient support. We aimed at designing an ankle and foot immobilizing device and measuring its efficacy at improving image fusion. Methods: We enrolled 20 patients undergoing distal lower-limb SPECT/CT of the ankle and the foot with and without a foot holder. The misalignment between SPECT and CT images was computed by manually measuring 14 fiducial markers chosen among anatomical landmarks also visible on bone scintigraphy. Analysis of variance was performed for statistical analysis. Results: The obtained absolute average difference without and with support was 5.1±5.2 mm (mean±SD) and 3.1±2.7 mm, respectively, which is significant (p<0.001). Conclusion: The introduction of the foot holder significantly decreases misalignment between SPECT and CT images, which may have clinical influence in the precise localization of foot and ankle pathology.
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In the last decade, local image features have been widely used in robot visual localization. In order to assess image similarity, a strategy exploiting these features compares raw descriptors extracted from the current image with those in the models of places. This paper addresses the ensuing step in this process, where a combining function must be used to aggregate results and assign each place a score. Casting the problem in the multiple classifier systems framework, in this paper we compare several candidate combiners with respect to their performance in the visual localization task. For this evaluation, we selected the most popular methods in the class of non-trained combiners, namely the sum rule and product rule. A deeper insight into the potential of these combiners is provided through a discriminativity analysis involving the algebraic rules and two extensions of these methods: the threshold, as well as the weighted modifications. In addition, a voting method, previously used in robot visual localization, is assessed. Furthermore, we address the process of constructing a model of the environment by describing how the model granularity impacts upon performance. All combiners are tested on a visual localization task, carried out on a public dataset. It is experimentally demonstrated that the sum rule extensions globally achieve the best performance, confirming the general agreement on the robustness of this rule in other classification problems. The voting method, whilst competitive with the product rule in its standard form, is shown to be outperformed by its modified versions.
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Nowadays the incredible grow of mobile devices market led to the need for location-aware applications. However, sometimes person location is difficult to obtain, since most of these devices only have a GPS (Global Positioning System) chip to retrieve location. In order to suppress this limitation and to provide location everywhere (even where a structured environment doesn’t exist) a wearable inertial navigation system is proposed, which is a convenient way to track people in situations where other localization systems fail. The system combines pedestrian dead reckoning with GPS, using widely available, low-cost and low-power hardware components. The system innovation is the information fusion and the use of probabilistic methods to learn persons gait behavior to correct, in real-time, the drift errors given by the sensors.
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Nowadays there is an increase of location-aware mobile applications. However, these applications only retrieve location with a mobile device's GPS chip. This means that in indoor or in more dense environments these applications don't work properly. To provide location information everywhere a pedestrian Inertial Navigation System (INS) is typically used, but these systems can have a large estimation error since, in order to turn the system wearable, they use low-cost and low-power sensors. In this work a pedestrian INS is proposed, where force sensors were included to combine with the accelerometer data in order to have a better detection of the stance phase of the human gait cycle, which leads to improvements in location estimation. Besides sensor fusion an information fusion architecture is proposed, based on the information from GPS and several inertial units placed on the pedestrian body, that will be used to learn the pedestrian gait behavior to correct, in real-time, the inertial sensors errors, thus improving location estimation.
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Resumo Este trabalho encontra-se dividido em três capítulos distintos. No primeiro, é caracterizada a doença degenerativa lombar, demorando-se o autor na descrição pormenorizada das alterações anatómicas, biomecânicas, e bioquímicas inerentes à sua ocorrência. Segue-se a descrição da evolução das diferentes formas de terapêutica, enumerando as que de forma clássica mais frequentemente são utilizadas (cirúrgicas e não cirúrgicas). No segundo capítulo, são referidos os mais recentes avanços tecnológicos nesta área, mencionando, nas suas vertentes biomecânicas, clínicas e terapêuticas, as particularidades das estabilizações dinâmicas interespinhosas e pediculares, bem como da artroplastia de disco. Após esta longa introdução, inicia-se o terceiro capítulo no qual se apresenta um estudo prospectivo da avaliação clínica, funcional, imagiológica e da variação da densidade mineral óssea vertebral em 20 doentes com patologia degenerativa, tratados com sistemas de estabilização dinâmica semi-rígida interespinhosa, e seguidos durante dois anos. Do estudo realizado conclui-se que os sistemas referidos são eficazes clínica e funcionalmente no tratamento de doentes com doença degenerativa lombar. Mais ainda, estes instrumentais proporcionam um aumento da altura do disco confirmado na incidência radiográfica de perfil no nível instrumentado. Constatámos ainda que a densidade mineral óssea vertebral dos doentes intervencionados, avaliada com sistema DXA, não demonstra diferenças com significância estatística ao longo do tempo, omparativamente à determinada em idêntica população mas sem qualquer patologia lombar. Acresce que se obteve uma correlação entre a funcionalidade física e a BMD radial, com significância estatística crescente nas duas medições realizadas. Abstract This study is divided in three different chapters. In the first one the author describes the anatomical, biomechanical and biochemical changes that go along with degenerative lumbar spine disease. The therapeutically possibilities are mentioned, mainly with the classic fusion and decompression as well as the non surgical options. Then, in the second chapter, the author describes, from the biomechanical, clinical and therapeutically point of view, the new techniques of dynamic stabilization, interspinous and pedicular systems, as well as disc replacement. After this introduction, in the third chapter a prospective clinical, functional, imagiologic and vertebral bone mineral density variation study is presented. Twenty patients with degenerative lumbar spine disease are selected, and operated with a semi rigid interspinous system device, and followed for a two year period. The author concludes that the interspinous semi rigid systems were clinically and functionally effective in lumbar degenerative patients. It was also founded that the disc height at the implant segment level increased after surgery. Bone density was assessed with a DXA system device. As far as vertebral bone density is concerned, the author found no differences what so ever inside the group during the study, or to an identical control group without any lumbar pathology. The correlation study between the BMD and physical function showed that there was only significant statistically data in radial BMD measurement, and this happened with growing correlation from year 2006 to 2007.
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Dissertação apresentada para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
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Fundação para a Ciência e Tecnologia - SFRH/BD/48804/2008 and the project PTDC/BI/65383/2006 assigned to Prof. Cecíla Roque and also to Associate Laboratory REQUIMTE (Pest-C/EQB/LA0006/2011)
Resumo:
The authors report the magnetic resonance imaging diagnostic features in two cases with respectively lumbar epidural hematoma and cavernous hemangioma of the lumbar epidural space. Enhanced MRI T1-weighted scans show a hyperintense signal rim surrounding the vascular lesion. Non-enhanced T2-weighted scans showed hyperintense signal.
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This paper presents a methodology based on the Bayesian data fusion techniques applied to non-destructive and destructive tests for the structural assessment of historical constructions. The aim of the methodology is to reduce the uncertainties of the parameter estimation. The Young's modulus of granite stones was chosen as an example for the present paper. The methodology considers several levels of uncertainty since the parameters of interest are considered random variables with random moments. A new concept of Trust Factor was introduced to affect the uncertainty related to each test results, translated by their standard deviation, depending on the higher or lower reliability of each test to predict a certain parameter.
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A search for a charged Higgs boson, H±, decaying to a W± boson and a Z boson is presented. The search is based on 20.3 fb−1 of proton-proton collision data at a center-of-mass energy of 8 TeV recorded with the ATLAS detector at the LHC. The H± boson is assumed to be produced via vector-boson fusion and the decays W±→qq′¯ and Z→e+e−/μ+μ− are considered. The search is performed in a range of charged Higgs boson masses from 200 to 1000 GeV. No evidence for the production of an H± boson is observed. Upper limits of 31--1020 fb at 95% CL are placed on the cross section for vector-boson fusion production of an H± boson times its branching fraction to W±Z. The limits are compared with predictions from the Georgi-Machacek Higgs Triplet Model.
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Olive oil quality grading is traditionally assessed by human sensory evaluation of positive and negative attributes (olfactory, gustatory, and final olfactorygustatory sensations). However, it is not guaranteed that trained panelist can correctly classify monovarietal extra-virgin olive oils according to olive cultivar. In this work, the potential application of human (sensory panelists) and artificial (electronic tongue) sensory evaluation of olive oils was studied aiming to discriminate eight single-cultivar extra-virgin olive oils. Linear discriminant, partial least square discriminant, and sparse partial least square discriminant analyses were evaluated. The best predictive classification was obtained using linear discriminant analysis with simulated annealing selection algorithm. A low-level data fusion approach (18 electronic tongue signals and nine sensory attributes) enabled 100 % leave-one-out cross-validation correct classification, improving the discrimination capability of the individual use of sensor profiles or sensory attributes (70 and 57 % leave-one-out correct classifications, respectively). So, human sensory evaluation and electronic tongue analysis may be used as complementary tools allowing successful monovarietal olive oil discrimination.