Um Modelo para Acompanhamento de Pessoas com Doença de Alzheimer utilizando Análise de Históricos de Contextos
DOI:
https://doi.org/10.5753/isys.2022.2226Keywords:
Doença de Alzheimer, Históricos de Contextos, Predição de Contextos, Monitoramento de Pacientes, Internet das Coisas para Cuidados com a SaúdeAbstract
Este artigo apresenta um modelo que considera dados fisiológicos recebidos de aplicativos externos, que possibilitam a identificação de possíveis comportamentos perigosos de pacientes com a Doença de Alzheimer (DA). A principal contribuição científica deste trabalho é a especificação de um modelo com foco na DA a partir da análise de Históricos de Contextos e Predição de Contextos. O modelo proposto DCARE é baseado no método de pesquisa experimental, para entender a doença e encontrar soluções que minimizem seu impacto no acompanhamento diário dos pacientes. De modo complementar, foi desenvolvido um simulador, que gera datasets para realizar testes do modelo, além de ser proposta uma ontologia para o tratamento de contextos na temática do Alzheimer. Este artigo consiste em uma versão estendida do trabalho publicado no Simpósio Brasileiro de Sistemas de Informação (SBSI) em 2021. Os cenários utilizados na construção do modelo foram elaborados a partir de entrevistas com cinco especialistas no atendimento a pacientes com DA. Os testes foram realizados com a massa de dados com 1026 amostras geradas pelo simulador proposto por este trabalho. Os resultados revelaram que as previsões dos cenários do modelo atingiram o objetivo do trabalho, obtendo 97,44% de acurácia.
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