Implementation and Evaluation of A Type-1 Fuzzy Logic Controller for Healthcare Diagnosis and Monitoring

Abstract

Type-1 fuzzy inference systems have shown potential to improve clinician performance by imitating human thought processes in complex circumstances and accurately executing repetitive tasks to which humans are ill-suited. This paper addresses the implementation of a type-1fuzzy model for pregnancy health risk diagnosis and monitoring to enhance control strategies in the medical discipline of diagnosis and monitoring pregnancy health conditions. Twenty-five pregnant patients are selected and studied and the observed results computed in the range of predefined limit by the domain experts. Both the design model and simulation result are same. The system is developed using NETBEANS IDE, JAVA, MYSQL, etc using Windows Vista as operating system platform. Results indicate that, the study has ascertained the association of the risk factors with pregnancy outcomes. It is observed that, the paper will serve as a tool for medical practitioners in educating the women more about the degree of influence of risk on pregnancy impacted by pregnancy risk factors. Thus encourage them to begin antenatal clinic early in pregnancy. It is believed that our application will reduce doctors’ workload during consultation and help to eradicate major negative pregnancy outcomes; thus promoting positive pregnancy outcomes.

Keywords: Type-1 fuzzy inference system, Fuzzy logic decision support, Pregnancy health risk, Infant mortality