Interval Type-2 Fuzzy Logic Based Decision Support System for Cardiac Risk Assessment

Gujarathi Trupti () and Bhole Kalyani ()
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Gujarathi Trupti: College of Engineering Pune, Department of Instrumentation and Control Engineering
Bhole Kalyani: College of Engineering Pune, Department of Instrumentation and Control Engineering

A chapter in New Trends in Computational Vision and Bio-inspired Computing, 2020, pp 995-1008 from Springer

Abstract: Abstract Cardiovascular diseases are commonly found all over the world. Patients having Cardiovascular risk (CVR) should not stop doing their daily activities without any fear or risk. This is achievable by continuous monitoring of the cardiovascular system to diagnose and avoid cardiovascular traumas such as cardiac arrest, in the minimum time. A little awareness and expert’s based decision support system would help patient to analyze the symptoms of cardiac arrest. This would help patient to get medical help as soon as possible and avoid the risk of cardiac arrest. In this paper, we designed a decision support system using fuzzy logic which allows us to represent the expert’s knowledge in terms of mathematics, accepting some level of uncertainties which lies within experts. Interval Type-2 based fuzzy logic system is designed and implemented using MATLAB. Developed system is tested on ten patients out of which eight patients diagnosis has validated with the test results. As this system is completely based on expert’s expertise, accuracy of the developed system depends on expert’s skill.

Keywords: Interval type-2 fuzzy inference; Membership function; Cardiac arrest; Risk assessment; Systolic blood pressure; Cholesterol; Heart rate; Blood sugar level (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-41862-5_101

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DOI: 10.1007/978-3-030-41862-5_101

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