Estudo da variação da frequência cerebral e relação entre ritmos lentos rápidos em registros de EEG comatosos e controles

• Ano de defesa: 2018
• Autor(a) principal: Oliveira, Cláudio Carrijo de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Uberlândia; Brasil; Programa de Pós-graduação em Engenharia Elétrica
• Palavras-chave em Português: Análise tempo-frequência; Brain Frequency Variation; Coma; Electroencephalography; Eletroencefalografia; Engenharia elétrica; OL/OR; Processamento de sinais; SW/FW; Time-frequency analysis; Variação da Frequência Cerebral; CNPQ::ENGENHARIAS::ENGENHARIA BIOMEDICA::BIOENGENHARIA::PROCESSAMENTO DE SINAIS BIOLOGICOS
• Link de acesso: https://repositorio.ufu.br/handle/123456789/21328; http://dx.doi.org/10.14393/ufu.di.2018.1105

The use of electroencephalography to aid in the diagnosis of unconsciousness in Intensive Care Units (ICU) environments is significantly used because it is a simple examination and low operational and monetary cost. From this, the analysis of this sign with the aim of associating possible coma etiologies with some of the patient's outcomes (living or dying) is essential and complex since there is little literature focused on this issue. Because it is a non-stationary signal, tools that use only the Fourier transform may not be applicable. Therefore, in this work an EEG processing technique that analyzes time and frequency, denominated Brain Frequency Variation (BFV) was applied in two databases of distinct EEG records: Coma (individuals hospitalized in the ICU) and Control (healthy people without neurological problems). For the Coma Group, 128 records were used and for the Control 100 records. It was noted that as the main result in the BFV analyzes that the variation of the Alpha rhythm (operating in a frequency range between 7.5 and 12.5 Hz) is higher in normal individuals, whereas that variation for the Delta rhythm (in the between 1 and 3.5 Hz) is higher in comatose patients. We also analyzed the quantification of BFV in the coma database, grouping and comparing different coma etiologies, and the main finding was that etiologies such as stroke and cranioencephalic trauma had different BFV patterns, indicating that the EEG tracing for each is different. A second quantifier was the relationship between slow (Delta and Theta) and fast (Alpha and Beta) rhythms, taking into account the power spectral density of the signal evaluated. It was noted that, as the main finding, the EEG records of comatose patients presented high rates of slow rhythms compared to the control group. Therefore, from the results obtained by the processing using these two tools, the comatose EEG signal can be evaluated with the intention of assisting in the prognosis of patients in ICU so that problems such as the diagnosis of death within this environment can be mitigated.