21 resultados para brain-computer interface
em Repositório Científico do Instituto Politécnico de Lisboa - Portugal
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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de redes de Comunicação e Multimédia
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A presente dissertação apresenta o desenvolvimento de um medidor de componentes passivos RLC. Este medidor baseia-se num protótipo desenvolvido para possibilitar a medição da impedância de um dispositivo em teste. Tendo uma carta de aquisição de sinal como interface, o protótipo comunica com um computador que controla todo o processo de medição desde a aquisição e processamento de sinais ao cálculo e visualização dos parâmetros. A topologia de medição implementada é a da ponte auto-balanceada e no processamento recorre-se ao método da desmodulação síncrona ou coerente. A sua viabilidade é suportada por um estudo teórico prévio, pela discussão das opções tomadas no projecto e pelos resultados obtidos através do algoritmo desenvolvido utilizando o software LabVIEW de programação gráfica.
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O presente trabalho final de mestrado refere-se ao estágio curricular realizado no âmbito do Mestrado de Engenharia Civil no ramo de edificações no Instituto Superior de Engenharia de Lisboa. O estágio decorreu na empresa ENGEXPOR Consultores de Engenharia, S.A. na obra do edifício de escritórios Metropólis Interface Sul – ZON Multimédia centrando-se principalmente na empreitada de acabamentos, revestimentos e instalações técnicas especiais, o qual decorreu entre os meses de Fevereiro e Setembro de 2012. Durante o estágio a aluna foi integrada numa equipa jovem, dinâmica e pró-ativa, onde desempenhou diversas funções de gestão, coordenação e acompanhamento dos trabalhos da envolvente exterior do edifício, com o objetivo de desenvolvimento das suas competências, fundamentalmente de compreensão e análise dos processos construtivos, do projeto, das relações entre os vários intervenientes e garantia de qualidade.
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Pre-operative diffusion tensor (DT) tractography is currently employed in our institutions. We use it to predict the course of the facial nerve (FN) in the vicinity of vestibular schwannomas (VS) of the cerebellopontine angle (CPA). In this study we were interested to assess the inter-observer reproducibility of this method. Two Neuroradiologists (PMGP and TT) determined independently the location of the FN by tractography and compared the results with in-vivo findings of microsurgery of VS.
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Relevant past events can be remembered when visualizing related pictures. The main difficulty is how to find these photos in a large personal collection. Query definition and image annotation are key issues to overcome this problem. The former is relevant due to the diversity of the clues provided by our memory when recovering a past moment and the later because images need to be annotated with information regarding those clues to be retrieved. Consequently, tools to recover past memories should deal carefully with these two tasks. This paper describes a user interface designed to explore pictures from personal memories. Users can query the media collection in several ways and for this reason an iconic visual language to define queries is proposed. Automatic and semi-automatic annotation is also performed using the image content and the audio information obtained when users show their images to others. The paper also presents the user interface evaluation based on tests with 58 participants.
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Liver steatosis is a common disease usually associated with social and genetic factors. Early detection and quantification is important since it can evolve to cirrhosis. In this paper, a new computer-aided diagnosis (CAD) system for steatosis classification, in a local and global basis, is presented. Bayes factor is computed from objective ultrasound textural features extracted from the liver parenchyma. The goal is to develop a CAD screening tool, to help in the steatosis detection. Results showed an accuracy of 93.33%, with a sensitivity of 94.59% and specificity of 92.11%, using the Bayes classifier. The proposed CAD system is a suitable graphical display for steatosis classification.
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Projeto para obtenção do grau de Mestre em Engenharia Informática e de Computadores
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Thesis submitted in the fulfilment of the requirements for the Degree of Master in Electronic and Telecomunications Engineering
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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica
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Os sistemas Computer-Aided Diagnosis (CAD) auxiliam a deteção e diferenciação de lesões benignas e malignas, aumentando a performance no diagnóstico do cancro da mama. As lesões da mama estão fortemente correlacionadas com a forma do contorno: lesões benignas apresentam contornos regulares, enquanto as lesões malignas tendem a apresentar contornos irregulares. Desta forma, a utilização de medidas quantitativas, como a dimensão fractal (DF), pode ajudar na caracterização dos contornos regulares ou irregulares de uma lesão. O principal objetivo deste estudo é verificar se a utilização concomitante de 2 (ou mais) medidas de DF – uma tradicionalmente utilizada, a qual foi designada por “DF de contorno”; outra proposta por nós, designada por “DF de área” – e ainda 3 medidas obtidas a partir destas, por operações de dilatação/erosão e por normalização de uma das medidas anteriores, melhoram a capacidade de caracterização de acordo com a escala BIRADS (Breast Imaging Reporting and Data System) e o tipo de lesão. As medidas de DF (DF contorno e DF área) foram calculadas através da aplicação do método box-counting, diretamente em imagens de lesões segmentadas e após a aplicação de um algoritmo de dilatação/erosão. A última medida baseia-se na diferença normalizada entre as duas medidas DF de área antes e após a aplicação do algoritmo de dilatação/erosão. Os resultados demonstram que a medida DF de contorno é uma ferramenta útil na diferenciação de lesões, de acordo com a escala BIRADS e o tipo de lesão; no entanto, em algumas situações, ocorrem alguns erros. O uso combinado desta medida com as quatro medidas propostas pode melhorar a classificação das lesões.
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The study of biosignals has had a transforming role in multiple aspects of our society, which go well beyond the health sciences domains to which they were traditionally associated with. While biomedical engineering is a classical discipline where the topic is amply covered, today biosignals are a matter of interest for students, researchers and hobbyists in areas including computer science, informatics, electrical engineering, among others. Regardless of the context, the use of biosignals in experimental activities and practical projects is heavily bounded by the cost, and limited access to adequate support materials. In this paper we present an accessible, albeit versatile toolkit, composed of low-cost hardware and software, which was created to reinforce the engagement of different people in the field of biosignals. The hardware consists of a modular wireless biosignal acquisition system that can be used to support classroom activities, interface with other devices, or perform rapid prototyping of end-user applications. The software comprehends a set of programming APIs, a biosignal processing toolbox, and a framework for real time data acquisition and postprocessing. (C) 2014 Elsevier Ireland Ltd. All rights reserved.
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Dissertação apresentada à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Audiovisual e Multimédia.
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Alzheimer Disease (AD) is characterized by progressive cognitive decline and dementia. Earlier diagnosis and classification of different stages of the disease are currently the main challenges and can be assessed by neuroimaging. With this work we aim to evaluate the quality of brain regions and neuroimaging metrics as biomarkers of AD. Multimodal Imaging Brain Connectivity Analysis (MIBCA) toolbox functionalities were used to study AD by T1weighted, Diffusion Tensor Imaging and 18FAV45 PET, with data obtained from the AD Neuroimaging Initiative database, specifically 12 healthy controls (CTRL) and 33 patients with early mild cognitive impairment (EMCI), late MCI (LMCI) and AD (11 patients/group). The metrics evaluated were gray-matter volume (GMV), cortical thickness (CThk), mean diffusivity (MD), fractional anisotropy (FA), fiber count (FiberConn), node degree (Deg), cluster coefficient (ClusC) and relative standard-uptake-values (rSUV). Receiver Operating Characteristic (ROC) curves were used to evaluate and compare the diagnostic accuracy of the most significant metrics and brain regions and expressed as area under the curve (AUC). Comparisons were performed between groups. The RH-Accumbens/Deg demonstrated the highest AUC when differentiating between CTRLEMCI (82%), whether rSUV presented it in several brain regions when distinguishing CTRL-LMCI (99%). Regarding CTRL-AD, highest AUC were found with LH-STG/FiberConn and RH-FP/FiberConn (~100%). A larger number of neuroimaging metrics related with cortical atrophy with AUC>70% was found in CTRL-AD in both hemispheres, while in earlier stages, cortical metrics showed in more confined areas of the temporal region and mainly in LH, indicating an increasing of the spread of cortical atrophy that is characteristic of disease progression. In CTRL-EMCI several brain regions and neuroimaging metrics presented AUC>70% with a worst result in later stages suggesting these indicators as biomarkers for an earlier stage of MCI, although further research is necessary.
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In this paper a new simulation environment for a virtual laboratory to educational proposes is presented. The Logisim platform was adopted as the base digital simulation tool, since it has a modular implementation in Java. All the hardware devices used in the laboratory course was designed as components accessible by the simulation tool, and integrated as a library. Moreover, this new library allows the user to access an external interface. This work was motivated by the needed to achieve better learning times on co-design projects, based on hardware and software implementations, and to reduce the laboratory time, decreasing the operational costs of engineer teaching. Furthermore, the use of virtual laboratories in educational environments allows the students to perform functional tests, before they went to a real laboratory. Moreover, these functional tests allow to speed-up the learning when a problem based approach methodology is considered. © 2014 IEEE.
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We present the modeling efforts on antenna design and frequency selection to monitor brain temperature during prolonged surgery using noninvasive microwave radiometry. A tapered log-spiral antenna design is chosen for its wideband characteristics that allow higher power collection from deep brain. Parametric analysis with the software HFSS is used to optimize antenna performance for deep brain temperature sensing. Radiometric antenna efficiency (eta) is evaluated in terms of the ratio of power collected from brain to total power received by the antenna. Anatomical information extracted from several adult computed tomography scans is used to establish design parameters for constructing an accurate layered 3-D tissue phantom. This head phantom includes separate brain and scalp regions, with tissue equivalent liquids circulating at independent temperatures on either side of an intact skull. The optimized frequency band is 1.1-1.6 GHz producing an average antenna efficiency of 50.3% from a two turn log-spiral antenna. The entire sensor package is contained in a lightweight and low-profile 2.8 cm diameter by 1.5 cm high assembly that can be held in place over the skin with an electromagnetic interference shielding adhesive patch. The calculated radiometric equivalent brain temperature tracks within 0.4 degrees C of the measured brain phantom temperature when the brain phantom is lowered 10. C and then returned to the original temperature (37 degrees C) over a 4.6-h experiment. The numerical and experimental results demonstrate that the optimized 2.5-cm log-spiral antenna is well suited for the noninvasive radiometric sensing of deep brain temperature.