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dc.contributor.authorLing, S.
dc.contributor.authorNguyen, H.
dc.contributor.authorChan, Kit Yan
dc.contributor.editorGary Fogel
dc.date.accessioned2017-01-30T15:10:09Z
dc.date.available2017-01-30T15:10:09Z
dc.date.created2011-03-13T20:01:59Z
dc.date.issued2010
dc.identifier.citationLing, Sai Ho and Nguyen, Hung and Chan, Kit Yan. 2010. Genetic Algorithm based Fuzzy Multiple Regression for the Nocturnal Hypoglycaemia Detection, in Fogel, G. (ed), IEEE Congress on Evolutionary Computation (CEC 2010), Jul 18 2010, pp. 1-6. Barcelona, Spain: IEEE.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/43787
dc.identifier.doi10.1109/CEC.2010.5586315
dc.description.abstract

Low blood glucose (Hypoglycaemia) is dangerous and can result in unconsciousness, seizures and even death. It has a common and serious side effect of insulin therapy in patients with diabetes. We measure physiological parameters (heart rate, corrected QT interval of the electrocardiogram (ECG) signal, change of heart rate, and the change of corrected QT interval) continuously to provide detection of hypoglycaemic. Based on these physiological parameters, we have developed a genetic algorithm based multiple regression model to determine the presence of hypoglycaemic episodes. Genetic algorithm is used to determine the optimal parameters of the multiple regression. The overall data were organized into a training set (8 patients) and a testing set (another 8 patient) which are randomly selected. The clinical results show that the proposed algorithm can achieve predictions with good sensitivities and acceptable specificities.

dc.publisherIEEE
dc.titleGenetic Algorithm based Fuzzy Multiple Regression for the Nocturnal Hypoglycaemia Detection
dc.typeConference Paper
dcterms.source.startPage1
dcterms.source.endPage6
dcterms.source.titleProceedings of the IEEE congress on evolutionary computation (CEC 2010)
dcterms.source.seriesProceedings of the IEEE congress on evolutionary computation (CEC 2010)
dcterms.source.conferenceIEEE Congress on Evolutionary Computation (CEC 2010)
dcterms.source.conference-start-dateJul 18 2010
dcterms.source.conferencelocationBarcelona, Spain
dcterms.source.placeSpain
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Copyright © 2010 IEEE This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

curtin.departmentDigital Ecosystems and Business Intelligence Institute (DEBII)
curtin.accessStatusOpen access


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