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A support vector machine for predicting spontaneous termination of paroxysmal atrial fibrillation episodes

Diaz, JD, Gonzalez, C and Escalona, OJ (2006) A support vector machine for predicting spontaneous termination of paroxysmal atrial fibrillation episodes. In: Computers in Cardiology 2006, Valencia, Spain, Valencia, Spain. Institute of Electrical and Electronics Engineers (IEEE). Vol 33 (1) 4 pp. [Conference contribution]

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URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4512010


The aim of this work is to predict the spontaneous termination of atrial fibrillation (AF) episodes. The database includes three record groups: non-terminating AF (N), AF that terminates one minute after recording end (S), and AF that terminates immediately after recording end (T). A first goal consisted on separating N from T group records (event 1), and a second, for separating S from T records (event 2). A Support Vector Machine was used for the classification problem. For event 1, four indexes were extracted: the atrial fibrillatory frequency (AFF) and the mean, standard deviation, and approximate entropy of RR intervals. For event 2, the AFF, the energy of the 3-7 Hz and 7-11 Hz bands, from the ten and five final seconds of the records, were used. The groups were divided in two sets: learning and test. For event 1, a 100% in learning, and 86.66% in test set were correctly classified. For the event 2, we classified 100% in the learning, and 80% in the test set.

Item Type:Conference contribution (Paper)
Keywords:Cardiology; Learning systems; Standards; Support vector machines; Testing; Vectors; Approximate entropy; Atrial fibrillation; Paroxysmal atrial fibrillation; R-R interval; Standard deviation; medical signal processing; signal classification.
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Engineering
Research Institutes and Groups:Engineering Research Institute
Engineering Research Institute > Nanotechnology & Integrated BioEngineering Centre (NIBEC)
ID Code:30029
Deposited By: Professor Omar Escalona
Deposited On:08 Feb 2016 14:22
Last Modified:08 Feb 2016 14:22

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