Sistema computacional para captura e avaliação da variabilidade da frequência cardíaca utilizando fotopletismografia

• Ano de defesa: 2020
• Autor(a) principal: Machado, Cesar Abascal
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; Brasil; Ciência da Computação; UFSM; Programa de Pós-Graduação em Ciência da Computação; Centro de Tecnologia
• Palavras-chave em Português: Fotopletismografia; Variabilidade da frequência cardíaca; Dispositivos portáteis de assistência médica; Monitoramento de saúde; Photoplethysmography; Heart rate variability; Portable healthcare devices; Health monitoring; CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: http://repositorio.ufsm.br/handle/1/22272

This work aimed to develop a computer system for capturing and assessing heart rate variability using the photoplethysmography technique. Its purpose is to enable monitoring and evaluation of health status in rehabilitation environments, with a low-cost and validated equipment. With technologies focused on health care, not only during exams and clinical routines, but also during physical exercise, providing vital information in real time. From similar equipment available and based on the literature, the prototype was developed. The system consists of a set of low cost hardware and software embedded and wireless communication, enabling greater practicality for its use and acquisition of photoplethysmography signals. The main physiological signals that the embedded system is able to monitor are heart rate, heart rate variability and peripheral blood oxygenation rate. To define the hardware and aiming at identifying and correcting problems, tests were first compared with similar equipment registered by Anvisa-BR and later collections of physiological signals were carried out with two groups: one of healthy volunteers and another with volunteers with chronic obstructive pulmonary disease to complement the validation of the embedded system. Finally, a dataset was developed to assist future studies in digital signal processing, as well as a low-cost computational algorithm for real-time processing of such signals.