Health Risk Early Detection Using Fuzzy Logic

Good life and health are interconnected concepts. Being healthy understand to prevent chronic diseases and illnesses as well as reduces the risk of premature death and improves the quality of life. But health crises significantly impact and change the way of life, such as the COVID-19 health crisis...

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Bibliographic Details
Main Authors: Prasandy, Teguh, Joni, Indrajani, Ying, Yi, Kusumawardhana, Indra
Format: Conference Proceeding
Language:English
Subjects:
Blood pressure
covid
COVID-19
design
detection
fuzzy
Fuzzy logic
Heart rate
Human factors
Mathematical models
MATLAB
Social factors
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Summary:Good life and health are interconnected concepts. Being healthy understand to prevent chronic diseases and illnesses as well as reduces the risk of premature death and improves the quality of life. But health crises significantly impact and change the way of life, such as the COVID-19 health crisis that changes people's behavior on protecting human life, social distancing, and care of wearing a face mask. Using the fuzzy logic method and MATLAB modeling, the function of this research has two folds. First, to propose a method for an early detection tool for COVID-19. Second, the findings' objective is to design an individual health crisis detection model that uses heart rate, SPO2, body temperature, cough frequency, and systolic blood pressure through MATLAB application with fuzzy logic features. Research data and validation sources from the COVID-19 patient data. The findings conclude that the fuzzy logic design that implements fuzzy features on MATLAB can make a prediction impact of covid with heart rate, SPO2, body temperature, cough frequency, and systolic blood pressure variables on low-risk, middle-risk, and high-risk infections.
ISSN:2837-2778
DOI:10.1109/ICIMTech59029.2023.10277909