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Development of a Fuzzy Logic-based Model for Monitoring Cardiovascular Risk

Author

Listed:
  • Peter Adebayo Idowu

    (Department of Computer Science and Engineering, Obafemi Awolowo University, Ile-Ife, Nigeria)

  • Sarumi Olusegun Ajibola

    (Department of Computer Science and Engineering, Obafemi Awolowo University, Ile-Ife, Nigeria)

  • Jeremiah Ademola Balogun

    (Department of Computer Science and Engineering, Obafemi Awolowo University, Ile-Ife, Nigeria)

  • Oluwadare Ogunlade

    (Department of Physiological Sciences, Obafemi Awolowo University, Ile-Ife, Nigeria)

Abstract

Cardiovascular diseases (CVD) are top killers with heart failure as one of the most leading cause of death in both developed and developing countries. In Nigeria, the inability to consistently monitor the vital signs of patients has led to the hospitalization and untimely death of many as a result of heart failure. Fuzzy logic models have found relevance in healthcare services due to their ability to measure vagueness associated with uncertainty management in intelligent systems. This study aims to develop a fuzzy logic model for monitoring heart failure risk using risk indicators assessed from patients. Following interview with expert cardiologists, the different stages of heart failure was identified alongside their respective indicators. Triangular membership functions were used to fuzzify the input and output variables while the fuzzy inference engine was developed using rules elicited from cardiologists. The model was simulated using the MATLAB® Fuzzy Logic Toolbox.

Suggested Citation

  • Peter Adebayo Idowu & Sarumi Olusegun Ajibola & Jeremiah Ademola Balogun & Oluwadare Ogunlade, 2015. "Development of a Fuzzy Logic-based Model for Monitoring Cardiovascular Risk," International Journal of Healthcare Information Systems and Informatics (IJHISI), IGI Global, vol. 10(4), pages 38-55, October.
    • Handle: RePEc:igg:jhisi0:v:10:y:2015:i:4:p:38-55
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