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Master's Dissertation
DOI
10.11606/D.3.2016.tde-30062016-075729
Document
Author
Full name
Tiago Sanches da Silva
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2016
Supervisor
Committee
Baccala, Luiz Antonio (President)
Augusto, Sergio Ribeiro
Coelho, Luiz Antonio Barbosa
Title in Portuguese
Plataforma de estudo para determinação de conectividade cerebral embarcada e em tempo real.
Keywords in Portuguese
Algoritmo embarcado
Análise de séries temporais
Coerência parcial direcionada
Conectividade cerebral
Eletroencefalografia
Medicina
Processamento em tempo real
Abstract in Portuguese
A presente dissertação examina um método de determinação da conectividade cerebral cujo uso vem se tornando popular nos últimos anos, o partial direct coherence (PDC), que se destaca dentre outros métodos por possibilitar a verificação das relações imediatas de sinais multivariados. Este método representa a conectividade cerebral no domínio da frequência e tem íntima relação com a noção de "causalidade" de Granger (GRANGER, 1969), que possibilita quantificar a influência mútua entre séries temporais observadas. De um ponto de vista computacional, o referido método faz uso de modelos de séries temporais que hoje têm implementação bastante eficiente em termos de algoritmos off-line, mas cujo sucesso depende da presunção de estacionariedade dos dados, fato que é somente verdadeiro em trechos relativamente curtos de sinais de origem cerebral, como no caso do EEG (Eletroencefalograma). O objetivo deste trabalho é criar um sistema que calcule o PDC, continuamente, em tempo real e que possua a mesma precisão do método off-line, além de ser uma plataforma de estudos para implementações e testes de métodos de determinação da conectividade neural em tempo real. A plataforma desenvolvida é modular, incentivando futuros trabalhos na mesma, e mostrouse eficaz quanto a precisão numérica dos resultados do cálculo do PDC. As características de tempo real foram atingidas com algumas restrições, que dependem da configuração do usuário e do número de canais que um sinal possui.
Title in English
Platform of study for embedded and real time determination of brain connectivity.
Keywords in English
Brain connectivity
Embedded algorithms
Medicine
Partial direct coherence
Real time processing
Abstract in English
This thesis examines a method of determination of brain connectivity whose use becomes popular in recent years, the partial direct coherence (PDC) that stands out in comparison with other methods for making possible the verification of immediate relations of multivariate signal. This method represents the brain connectivity in the frequency domain and has a close relationship with the notion of Granger causality (GRANGER, 1969) that makes it possible to quantify the mutual influence between observed time series. From a computational perspective, the above method makes use of time series models, which today has very efficient implementation in terms of off-line algorithm, but whose success depends on presume that the data is stationary, a fact that is only true in relatively short stretches of cerebral signals, especially in the case of EEG. The objective of this thesis is to create a system that calculates the PDC continuously and in real time maintaining the same precision of the off-line method. Furthermore being a research platform for implementations and tests of new methods for determining neural connectivity in real time. The developed platform is modular encouraging future work on it, and was effective in the numerical accuracy of the PDC calculation results. The real time characteristics were achieved with some restrictions that depend of the user configuration and the number of channels that the signal has.
 
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Publishing Date
2016-12-09
 
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