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A new approach for ICD rhythm classification based on support vector machines

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7 Author(s)
Kamousi, B. ; Sch. of Med., Stanford Univ., Stanford, CA, USA ; Tewfik, A. ; Lin, B. ; Al-Ahmad, A.
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Inappropriate shocks due to misclassification of supraventricular and ventricular arrhythmias remain a major problem in the care of patients with implantable cardioverter defibrillators (ICDs). The purpose of this study was to investigate the ability of a new covariance-based support vector machine classifier, to distinguish ventricular tachycardia from other rhythms such as supraventricular tachycardia. The proposed algorithm is applicable on both single and dual chamber ICDs and has a low computational demand. The results demonstrate that suggested algorithm has considerable promise and merits further investigation.

Published in:

Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE

Date of Conference:

3-6 Sept. 2009

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