Classificação de Hipertensos Utilizando o Sinal da Variabilidade da Frequência Cardíaca (VFC) com Auxílio de Inteligência Artificial

• Ano de defesa: 2022
• Autor(a) principal: Rafael Goncalves de Oliveira Viana
• Orientador(a): Milton Ernesto Romero Romero
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Fundação Universidade Federal de Mato Grosso do Sul
• País: Brasil
• Palavras-chave em Português: Variabilidade de Frequência Cardíaca, Sistema Nervoso Autônomo, Inteligência Artificial, Hipertensão
• Link de acesso: https://repositorio.ufms.br/handle/123456789/5439

The Autonomic Nervous System is one of those responsible for cardiovascular configurations and its enhancement can be measured using the Heart Rate Variability (HRV) by R waves, present in the Electrocardiogram. Currently, hypertension is highly prevalent in all countries. Thanks to smart wearable equipment, a cluster of data began to be collected and stored, however little explored. New methods of measuring hypertension using stored data help in the cardiovascular control of a large number of people. In this research, the HRV data collected by wearable equipment of low cost and of easy acquisition, were processed and a result of 75\% of accuracy was obtained when using artificial intelligence in the classification of medicated hypertensive and non-hypertensive patients (healthy ). This result is probably related to the effectiveness of the medication used by the patients. New research seeking candidates who suffer from altered blood pressure (not hypertensive) should be carried out in order to extract these characteristics, by not using blood pressure control medication.