Identifcação do padrão de hipsarritmia em eletroencefalogramas: utilizando decomposição de sinais em pequenas ondas

• Ano de defesa: 2019
• Autor(a) principal: SOUSA, Gean Carlos Lopes de
• Orientador(a): BARROS FILHO, Allan Kardec Duailibe
• Banca de defesa: BARROS FILHO, Allan Kardec Duailibe , FONSECA NETO, João Viana da , CARVALHO FILHO, Antonio Oseas de , SEQUERRA, Eduardo Bouth
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Maranhão
• Programa de Pós-Graduação: PROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA DE ELETRICIDADE/CCET
• Departamento: DEPARTAMENTO DE ENGENHARIA DA ELETRICIDADE/CCET
• País: Brasil
• Palavras-chave em Português: Hipsarritmia; Wavelet; Funções de Gabor; Gabor sintonizadas
• Palavras-chave em Inglês: Hypsarrhythmia; Wavelet; Gabor functions; Tuned Gabor
• Área do conhecimento CNPq: Teoria Eletromagnética, Microondas, Propagação de Ondas, Antenas; Clínica Médica; Análise de Algoritmos e Complexidade de Computação
• Link de acesso: https://tedebc.ufma.br/jspui/handle/tede/3024

Epilepsy is a temporary change in brain function.It is possible during an epileptic seizure to see marked changes. In infants, for example, some encephalopathies such as West syndrome stand out. West syndrome is mainly characterized by infantile spasms and hipsarrhythmia. Hypsarrhythmia, first described in 1952, is characterized by an electroencephalographic pattern composed of slow waves and high-voltage anarchic projection spicules. The pattern of hipsarrhythmia is also present in EEG's of children with microcephaly caused by Zika virus. Although the characteristics of hipsarrhythmia in the electroencephalogram are well defined, the identification of this pattern still causes disagreement among specialists. This work proposes the development of mathematical and computational methods capable of identifying the basic characteristics of this pathological electrical signal, in order to assist in the diagnosis and prognosis of epileptic patients. During this work we present the mathematical formulation of the continuous and discrete Wavelet Transform of the Gabor functions that will be used as the core of this transformation and the tuned Gabor functions. The calculation of the three indices in electroencephalogram signals of infants with Zika virus was applied to identify hipsarrhythmia. These signals were acquired from the Maranhão State Government project called Casa Ninar. The results may show the effectiveness of the methodology in identifying the pattern of hipsarrhythmia, since they present rates of accuracy that range from 95 to 100 % in the classification of electroencephalograms. In the most difficult task, which is to classify sections of the EEG, the hit rates ranged from 75 to 90 %.