Analítica de bioseñales para atención en casa en tiempo de emergencia sanitaria.

This research study focuses on analyzing vital signs of different pathologies, recreated by means of mannequin-type simulators, to generate a quick and effective diagnosis for home care monitoring during a health emergency such as COVID-19. A descriptive data analysis model (CRISP-DM) is implemented to examine changes in vital signs through the creation of an interactive visualization tool. This tool is designed with a graph for each vital sign, allowing assessing their changes independently to provide a general assessment of the patient's health. In addition, the tool also assembles all vital signs into a single graph to allow identification and analysis of every instant in which vital sign variations surpass normal parameters. In conclusion, the tool developed here provides visual and interactive support for health professionals, which allows them to make informed decisions, enhancing the traditional scheme of hospital services when preventing complications in the health of patients. [ABSTRACT FROM AUTHOR]