Cadastro, processamento e visualização de eletroencefalograma

• Ano de defesa: 2019
• Autor(a) principal: Barbosa, João Ludovico Maximiano
• 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 Biomédica
• Palavras-chave em Português: EEG; Processamento; Visualização; Cadastro; Engenharia biomédica; Processing; Visualization; Registration; CNPQ::ENGENHARIAS::ENGENHARIA BIOMEDICA::BIOENGENHARIA::PROCESSAMENTO DE SINAIS BIOLOGICOS
• Link de acesso: https://repositorio.ufu.br/handle/123456789/25432; http://dx.doi.org/10.14393/ufu.di.2019.2018

The electroencephalogram (EEG) make the electric reading of the cerebral scalp, but the values collected by it are only data that alone convey a message or meaning. However, when this data is processed and new data is associated with it, the EEG begins to bring some information. It can be used for diagnosis of neurological disorders, critical patient follow-up, as well as for applications of brain-machine interfaces among other applications. In this perspective, this work presents software for EEG processing that generates several quantifiers, and which has been improved in such a way that it needs only one input file in predetermined format, with a set of information needed to generate the quantifiers, and so it can process multiple EEG's without the continuous intervention of the researcher, who can perform other activities while processing is performed. The present work also contemplates a tool for generating topographic visualization of the quantifiers extracted in the processing, which allows comparisons between several EEGs and may be of different etiologies, and also shows the temporal evolution of the quantifier, these views are important because it facilitates analysis of results, since the EEG's have numerous data and understand them only in numerical form is not trivial. In addition, a platform was also built to register the EEG's collected by the research group, using spring-boot and react, which aims to facilitate the consultation and management of collected EEG, allowing greater dexterity in the selection of exams for conducting clinical studies.