152 research outputs found
Science 2.0 : sharing scientific data on the Grid
Mestrado em Engenharia de Computadores e TelemáticaA computação assumese
cada vez mais como um recurso essencial em
ciência, levando ao surgimento do termo eCiência
para designar a utilização
de tecnologias de computação avançada para suportar a realização de
experiências científicas, a preservação e partilha do conhecimento.
Uma das áreas de aplicação do conceito de eCiência
é o tratamento e análise
de imagens médicas. Os processos que lidam com imagem médica, tanto ao
nível clínico como de investigação, são exigentes em relação ao suporte
computacional, devido aos algoritmos de processamento de imagem que
requerem e à elevada capacidade de armazenamento relacionada com volume
das imagens geradas.
As políticas públicas e os avanços tecnológicos recentes orientados para a eCiência,
têm vindo a apoiar o desenvolvimento da computação em Grid, tanto
a nível dos middlewares como da instalação de capacidade de produção, como
um sistema de computação avançado que permite a partilha de recursos,
instrumentos científicos e boas práticas em comunidades virtuais.
Este trabalho tem como objectivo desenvolver uma estratégia e um protótipo
para o armazenamento de dados médicos na Grid, visando a sua utilização em
investigação. Uma preocupação diferenciadora prendese
com o objectivo de
colocar as potencialidades da Grid ao serviço de utilizadores não técnicos (e.g.
médicos, investigadores), que acedem a serviços de processamento e de
armazenamento e catalogação de dados de forma transparente, através de um
portal Web.
O protótipo desenvolvido permite a investigadores na área das neurociências,
sem conhecimentos específicos da tecnologia Grid, armazenar imagens e
analisálas
em Grids de produção existentes, baseadas no middleware gLite.
ABSTRACT: Computing has become an essential tool in modern science, leading to the
appearance of the term eScience
to designate the usage of advanced
computing technologies to support the execution of scientific experiments, and
the preservation and sharing of knowledge.
One of eScience
domain areas is the medical imaging analysis. The processes
that deal with medical images, both at clinical and investigation level, are very
demanding in terms of computational support, due to the analysis algorithms
that involve large volumes of generated images, requiring high storage
capabilities.
The recent public policies and technological advances are eScience
oriented,
and have been supporting the development of Grid computing, both at the
middleware level and at the installation of production capabilities in an
advanced computing system, that allows the sharing of resources, scientific
instrumentation and good practices among virtual communities.
The main objective of this work is to develop a strategy and a prototype to allow
the storage of medical data on the Grid, targeting a research environment. The
differentiating concern of this work is the ability to provide the nonexperts
users (e.g: doctors, researchers) access to the Grid services, like storage and
processing, through a friendly Web interface.
The developed prototype allows researchers in the field of neuroscience,
without any specific knowledge of Grid technology, to store images and analyse
them in production Grid infrastructures, based on the gLite middleware
The feasibility of an augment reality system to study the psychophysiological correlates of fear-related responses
Previous studies have successfully used augmented reality (AR) as an aid to exposure-based treatments for anxiety disorders. However, to the best of our knowledge, none of these studies have measured the physiological correlates of the fear response, relying solely on self-reports and behavioral avoidance tests.publishe
A Methodology for Creating an Adapted Command Language for Driving an Intelligent Wheelchair
Intelligent wheelchairs (IW) are technologies that can increase the autonomy and independence of elderly people and patients suffering from some kind of disability. Nowadays the intelligent wheelchairs and the human-machine studies are very active research areas. This paper presents a methodology and a Data Analysis System (DAS) that provides an adapted command language to an user of the IW. This command language is a set of input sequences that can be created using inputs from an input device or a combination of the inputs available in a multimodal interface. The results show that there are statistical evidences to affirm that the mean of the evaluation of the DAS generated command language is higher than the mean of the evaluation of the command language recommended by the health specialist (p value = 0.002) with a sample of 11 cerebral palsy users. This work demonstrates that it is possible to adapt an intelligent wheelchair interface to the user even when the users present heterogeneous and severe physical constraints
Multi-voxel fMRI analysis using an high throughput grid framework
Mestrado em Engenharia Biomédica - Instrumentação, Sinal e ImagemO presente trabalho apresenta uma nova abordagem à análise de imagens de RMf do cérebro, especificamente a utilização de medidas associativas na análise de séries temporais de RMf. Este tipo específico de análise, computacionalmente intensivo, requer recursos que normalmente não se encontram disponíveis em ambientes clínicos.
Redes Grid é um novo paradigma de computação distribuída de elevada performance que pode ser utilizado para potenciar a utilização deste tipo de
análise, disponibilizando a capacidade de computação necessária.
Implementouse um framework que permite a utilização de uma infraestrutura Grid para correr este tipo de análise de forma transparente, viabilizando a sua utilização em ambientes clínicos, onde o tempo é um factor crítico.
ABSTRACT: This work, introduces a new approach to fMRI brain image analysis, namely multivoxel
fMRI association analysis. The problem associated with this type of approach is that requires a large computing capacity that is not normally
available at clinical sites.
To enable this specific type of analysis we are required to use High Performance Computing paradigms. In this context we analysed the use of Grid computing and implemented a framework that allows running the multivoxel fMRI association analysis using a grid infrastructure resources. The use of this framework makes this type of analysis usable in clinical environments where time constraints can have a vital importance
A web portal for Portuguese brain imaging network
Mestrado em Engenharia de Computadores e TelemáticaA Imagiologia Cerebral (IC) está na fronteira entre a neurologia,
engenharia e física. écnicas de imagens médicas multimodais, tais como
a Ressonância Magnética (MRI e fMRI) e Espectroscopia (MRS),
Tomografia Computadorizada por Emissão de Fotões/Positrões
(SPECT/PET), entre outros, são emergentes ferramentas de pesquisa
médica que pode fornecer informações valiosas para o diagnóstico de
doenças do cérebro. Eletroencefalograma de alta resolução (HR-EEG),
técnicas para sincronizar e fundir seus resultados de análise e várias
técnicas de imagem são também parte de IC.
Em Portugal, dado o facto que a maioria das áreas relacionadas com
IC (por exemplo, medicina, engenharia ou física) são assuntos de
investigação em muitos grupos de P&D, um consórcio de universidades
de Aveiro, Coimbra, Minho e Porto criou a Rede Nacional de
Imagiologia Funcional Cerebral (RNIFC). A RNIFC é uma associação
sem fins lucrativos que foi formalizada e assinada em fevereiro de 2009.
Actualmente, com o suporte de sistemas digitais para armazenar
imagens médicas, é possível partilhar dados entre essas instituições para
melhorar o diagnóstico, e permitir investigações entre a comunidade
médica de diferentes instituições.
O principal objectivo desta dissertação é descrever a implementação
dos serviços de sistemas de informação essenciais para a Brain Imaging
Network (BIN) que suportam actualmente o RNIFC acessível através do
Portal BIN, o principal ponto de entrada para a BING. O Portal BIN
permite aos pesquisadores na comunidade BING espalhadas pelo país e
no estrangeiro, quer para solicitar o acesso a instrumentos científicos ou
para recuperar os seus casos e executar as suas análises.
ABSTRACT: Brain Imaging is in the frontier between neurology, engineering and
physics. Multimodal medical imaging techniques, such as Magnetic
Resonance Imaging (MRI and fMRI) and Spectroscopy (MRS), Single
Photon/Positron Emitting Tomography (SPECT/PET) among others, are
emergent medical research tools that can provide valuable information
for diagnosis of brain diseases. High-resolution electroencephalogram
(HR-EEG), techniques for synchronizing and fuse its analysis results and
several imaging techniques are also part of BI.
In Portugal, given fact that most of the BI related areas (e.g. medical,
engineering or physics) are subjects of research in many R&D groups, a
consortium of the universities of Aveiro, Coimbra, Minho and Porto
created the National Functional Brain Imaging Network (RNIFC). The
RNIFC is a non-profitable association that was formalized and signed in
February 2009.
Currently, with the support of digital systems to store medical images,
it is possible to share data among these institutions to improve diagnosis,
and allow investigations by the medical community among different
institutions.
The main objective of this thesis is to describe the implementation of
the essential Brain Imaging Network (BIN) information systems services
that currently support the RNIFC accessible through the BIN Portal, the
main entry point for the BING. BIN Portal enables researchers in the
BING community scattered along the country and abroad either to apply
for access to the scientific instruments or to retrieve their cases and run
their analysis
Relación entre la farmacocinética y los cambios hemodinámicos durante la inducción y posicionamiento en pacientes quirúgicos anestesiados con propofol
Tesis por compendio de publicaciones[EN]For long years, it was thought that anaesthetic management did not influence
patient’s outcome. Surgical morbidity and long-term mortality were attributed to
patient’s comorbidity, malignance of the disease, risk infection and type of surgery.
Nowadays, there is an increasing evidence that intraoperative anaesthetic
management can influence long-term patient outcomes. In the last two decades,
surgical mortality rates have been falling and, in part, this is due to a huge
improvement in anaesthesia related factors and safety. For an anaesthesiologist,
perioperative care is no longer the simple fact of administrating the anaesthetic drug
and maintaining the patient “asleep”. Direct-guided fluid therapy, maintaining
intraoperative normothermia, minimizing blood transfusion and avoiding low mean
arterial pressure and deep hypnotic level are additional procedures the
anaesthesiologist is responsible for and that will probably improve patient’s outcome
and decrease surgical mortality.
Hypotension after induction of anaesthesia is quite common and more prevalent
during the late post-induction period and before skin incision (5-10 minutes after),
generally thought to be clinically irrelevant. Nowadays, there is some evidence that
small haemodynamic changes, such as hypotension, even for small periods, are
associated with poor patient outcomes, because they have the potential to cause
an ischemia–reperfusion injury which may be manifested as dysfunction of any vital
organ, like acute kidney and myocardial injury. Intra-operative management of
hypotension is usually guided by conventional monitoring (systolic blood pressure and
MAP) but these parameters could mask low levels of blood flow and oxygen delivery,
even for short periods, leading to major surgical complications and longer hospital
stays
Preface - Creativity and HCI: From Experience to Design in Education
Abstract included in text
Individual EEG differences in affective valence processing in women with low and high neuroticism
Objective: In this study, individual differences in brain electrophysiology during positive and negative
affective valence processing in women with different neuroticism scores are quantified.
Methods: Twenty-six women scoring high and low on neuroticism participated on this experiment. A
support vector machine (SVM)-based classifier was applied on the EEG single trials elicited by high arousal pictures with negative and positive valence scores. Based on the accuracy values obtained from subject identification tasks, the most distinguishing EEG channels among participants were detected,
pointing which scalp regions show more distinct patterns.
Results: Significant differences were obtained, in the EEG heterogeneity between positive and negative
valence stimuli, yielding higher accuracy in subject identification using negative pictures. Regarding
the topographical analysis, significantly higher accuracy values were reached in occipital areas and in
the right hemisphere (p < 0:001).
Conclusions: Mainly, individual differences in EEG can be located in parietooccipital regions. These differences are likely to be due to the different reactivity and coping strategies to unpleasant stimuli in individuals with high neuroticism. In addition, the right hemisphere shows a greater individual specificity.
Significance: An SVM-based classifier asserts the individual specificity and its topographical differences in
electrophysiological activity for women with high neuroticism compared to low neuroticism
- …