Title :
A new approach for ICD rhythm classification based on support vector machines
Author :
Kamousi, Baharan ; Tewfik, Ahmed ; Lin, Bryant ; Al-Ahmad, Amin ; Hsia, Henry H. ; Zei, Paul C. ; Wang, Paul J.
Author_Institution :
Sch. of Med., Stanford Univ., Stanford, CA, USA
Abstract :
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.
Keywords :
bioelectric phenomena; covariance analysis; defibrillators; medical signal processing; signal classification; support vector machines; ICD rhythm classification; covariance-based SVM classifier; dual chamber ICD; implantable cardioverter defibrillator; patient care; single chamber ICD; support vector machines; supraventricular arrhythmias; ventricular arrhythmias; ventricular tachycardia; Algorithms; Arrhythmias, Cardiac; Cardiology; Computer Simulation; Defibrillators, Implantable; Electrocardiography; Heart Rate; Humans; Pattern Recognition, Automated; Reproducibility of Results; Signal Processing, Computer-Assisted; Software; Tachycardia, Ventricular; Therapy, Computer-Assisted;
Conference_Titel :
Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
Conference_Location :
Minneapolis, MN
Print_ISBN :
978-1-4244-3296-7
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2009.5334794