A Fuzzy Rule-Based Model for Remote Monitoring of Preterm in the Intensive Care Unit of Hospitals

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dc.contributor.authorEmuoyibofarhe, Justice O.en_US
dc.contributor.authorAkindele, Akinyinka T.en_US
dc.contributor.authorRonke, Babatunde S.en_US
dc.contributor.authorOmotosho, Adebayoen_US
dc.contributor.authorMeinel, Christophen_US
dc.date.accessioned2020-09-24T07:51:57Z
dc.date.available2020-09-24T07:51:57Z
dc.date.issued2019-05
dc.description.abstractThe use of Remote patient monitoring (RPM) systems to monitor critically ill patients in the Intensive Care Unit (ICU) has enabled quality and real-time healthcare management. Fuzzy logic as an approach to designing RPM systems provides a means for encapsulating the subjective decision-making process of medical experts in an algorithm suitable for computer implementation. In this paper, a remote monitoring system for preterm in neonatal ICU incubators is modeled and simulated. The model was designed with 4 input variables (body temperature, heart rate, respiratory rate, and oxygen level saturation), and 1 output variable (action performed represented as ACT). ACT decides whether an alert is generated or not and also determines the message displayed when a notification is required. ACT classifies the clinical priority of the monitored preterm into 5 different fields: code blue, code red, code yellow, code green, and code black. The model was simulated using a fuzzy logic toolbox of MATLAB R2015A. About 216 IF_THEN rules were formulated to monitor the inputs data fed into the model. The performance of the model was evaluated using the confusion matrix to determine the model’s accuracy, precision, sensitivity, specificity, and false alarm rate. The experimental results obtained shows that the fuzzy-based system is capable of producing satisfactory results when used for monitoring and classifying the clinical statuses of neonates in ICU incubators.en_US
dc.identifier.affiliationsLadoke Akintola University of Technology, Ogbomoso, Nigeriaen_US
dc.identifier.affiliationsDepartment of Computer Science, Kwara State University, Malette, Nigeriaen_US
dc.identifier.affiliationsLandmark University, Omuaran, Kwara State, Nigeriaen_US
dc.identifier.affiliationsHasso Plattner Institute, University of Potsdam, Potsdam, Germanyen_US
dc.identifier.citationEmuoyibofarhe Justice O., Akindele Akinyinka T., Ronke Babatunde S., Omotosho Adebayo, Meinel Christoph. A Fuzzy Rule-Based Model for Remote Monitoring of Preterm in the Intensive Care Unit of Hospitals. International Journal of Medical Research & Health Sciences. 2019 May; 8(5): 33-44en_US
dc.identifier.issn2319-5886
dc.identifier.placeIndiaen_US
dc.identifier.urihttps://imsear.searo.who.int/handle/123456789/204917
dc.languageenen_US
dc.publisherSumathi Publicationsen_US
dc.relation.issuenumber5en_US
dc.relation.volume8en_US
dc.source.urihttps://www.ijmrhs.com/abstract/a-fuzzy-rulebased-model-for-remote-monitoring-of-preterm-in-the-intensive-care-unit-of-hospitals-18388.htmlen_US
dc.subjectRemote patient monitoringen_US
dc.subjectFuzzy logicen_US
dc.subjectPretermen_US
dc.subjectIncubatoren_US
dc.subjectConfusion matrixen_US
dc.titleA Fuzzy Rule-Based Model for Remote Monitoring of Preterm in the Intensive Care Unit of Hospitalsen_US
dc.typeJournal Articleen_US
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