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Master's Dissertation
DOI
10.11606/D.74.2005.tde-06072005-111659
Document
Author
Full name
Ana Carolina de Sousa Silva
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
Pirassununga, 2005
Supervisor
Committee
Costa, Ernane José Xavier (President)
Itiki, Cinthia
Titto, Evaldo Antonio Lencioni
Title in Portuguese
Aplicação de técnicas de processamento digital de sinais na caracterização de sinais cerebrais de bovinos
Keywords in Portuguese
bovinos
densidade espectral de potências
EEG
estresse térmico
filtros digitais
ondaletas
Abstract in Portuguese
A aquisição de sinais cerebrais de bovinos adultos, utilizando um equipamento de transmissão telemétrica dos dados e eletrodos de superfície, foi avaliada neste trabalho através de técnicas de processamento digital de sinais. Foram estudados a melhor disposição dos eletrodos, diferentes métodos de remoção de artefatos e as características em freqüência do sinal. A remoção de artefatos foi feita de duas maneiras: (1) uso de um filtro que substituía valores extremos do sinal por seu valor médio e (2) decomposição utilizando a capacidade de multiresolução das ondaletas. Os resultados obtidos mostraram que apenas trechos de sinal livres de artefatos podem ser processados. O processamento indicou faixas de freqüências em acordo com a literatura. A metodologia usada neste trabalho mostrou-se suficiente para concluir que é possível monitorar e analisar sinais cerebrais de bovinos adultos que podem se mover livremente, sem acrescentar ao experimento o estresse característico de contenção
Title in English
Digital signal processing techniques applied to bovine brain electrical activity monitoring
Keywords in English
bovines
digital filters
EEG
heat stress
power spectral density
wavelets
Abstract in English
Acquisition of brain electrical activity from grown bovines, using a telemetric data transmitter system and scalp electrodes, was evaluated in this work. Electrodes placement, different artifact removal methodologies and signal frequency component were studied. Artifacts removal was carried out in two different ways: (1) by means of a filter that replaced elevated amplitude points for the signal’s mean value and (2) decomposition using wavelet multiresolution capability. Results using filters show that only artifact-free signal stretches can be processed. The processing indicated that frequency ranges are in agreement with literature. The methodology applied in this work is enough to conclude that it is possible to analyze brain electrical signal from grown bovines that can move freely, without add restrain stress factors to experiment
 
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Publishing Date
2005-07-06
 
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