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Electrocardiographic Signals and Swarm-Based Support Vector Machine for Hypoglycemia Detection.
MedLine Citation:
PMID:  22012087     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Cardiac arrhythmia relating to hypoglycemia is suggested as a cause of death in diabetic patients. This article introduces electrocardiographic (ECG) parameters for artificially induced hypoglycemia detection. In addition, a hybrid technique of swarm-based support vector machine (SVM) is introduced for hypoglycemia detection using the ECG parameters as inputs. In this technique, a particle swarm optimization (PSO) is proposed to optimize the SVM to detect hypoglycemia. In an experiment using medical data of patients with Type 1 diabetes, the introduced ECG parameters show significant contributions to the performance of the hypoglycemia detection and the proposed detection technique performs well in terms of sensitivity and specificity.
Authors:
Nuryani Nuryani; Steve S H Ling; H T Nguyen
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2011-10-20
Journal Detail:
Title:  Annals of biomedical engineering     Volume:  -     ISSN:  1521-6047     ISO Abbreviation:  -     Publication Date:  2011 Oct 
Date Detail:
Created Date:  2011-10-20     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0361512     Medline TA:  Ann Biomed Eng     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Affiliation:
Faculty of Engineering and Information Technology, University of Technology Sydney, City Campus, 15 Broadway Road, Ultimo, NSW, 2007, Australia, nnuryani@eng.uts.edu.au.
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