Cardiac arrhythmia beat classification using DOST and PSO tuned SVM

• A new method is proposed in this manuscript for the classification of cardiac arrhythmia beats. Algorithms used in this method are Pan-Tompkins algorithm for R-peak detection, discrete orthogonal stockwell transform (DOST) for feature extraction of ECG signals, support vector machines (SVMs) for classification whose parameters are tuned using particle swarm optimization (PSO) technique for automatic cardiac arrhythmia beat classification.• The best performance parameters for the SVM classifier are selected by employing PSO technique to achieve maximum accuracy.

Source: Computer Methods and Programs in Biomedicine - August 28, 2016 Category: Bioinformatics Authors: Sandeep Raj, Kailash Chandra Ray, Om Shankar Source Type: research