Uma plataforma para integração de dispositivos de saúde em sistemas de monitoramento remoto de pacientes
Ano de defesa: | 2023 |
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Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | |
Tipo de documento: | Tese |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Federal do Espírito Santo
BR Doutorado em Ciência da Computação Centro Tecnológico UFES Programa de Pós-Graduação em Informática |
Programa de Pós-Graduação: |
Não Informado pela instituição
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Departamento: |
Não Informado pela instituição
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País: |
Não Informado pela instituição
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Palavras-chave em Português: | |
Link de acesso: | http://repositorio.ufes.br/handle/10/17246 |
Resumo: | The increase in the number of people with a chronic health condition has led researchers from different areas to seek alternatives for monitoring these patients outside the hospital environment, in order to monitor them continuously and prevent the worsening of their health status. In this sense, one research topic rising is RPM (Remote Patient Monitoring). This approach allows monitoring the health condition of patients from a distance, helping to prevent new hospitalization episodes, and improving their quality of life, and the care administered by health providers. However, the currently available RPM solutions face some challenges, mainly in the integration of new devices. Usually, solutions are designed for a specific scenario and do not focus on problems related to the heterogeneity of devices available for health monitoring. A solution that provides means for the integration of new devices has the potential to collaborate in advancing the state of the art in research in this context. Therefore, this thesis proposes a solution to support the execution of RPM projects, composed of a reference architecture and its implementation, materialized as the HDash Remote Monitoring Platform. HDash implements the proposed conceptual architecture, providing means for new devices to be easily integrated in order to meet different application scenarios. To evaluate the approach, two case studies were conducted: the first monitoring chronic patients, followed for 20 months, and the second monitoring in remote locations, for 36 months. The studies allowed evaluation of several aspects of the proposed architecture and it is hoped, therefore, that this work can contribute to RPM and that new research in this context will benefit from the artifacts produced in this thesis. |