PVC Ectopic Beats Detection Using Genetic-based Support Machine and Features of QRS Wave

Abstract

Cardiac arrhythmia, being the key sign regarding heart disease monitored by ECG signals. By carefully analysing ECG signals, we can determine various classes of arrhythmia. PVC is ordinary form of arrhythmia. Diagnosis of PVC ectopic beats is done by using ECG signals which is crucial for the prognosis of probable heart failure. The strategy propounded in this article for PVCs detection is Genetic based SVM. The key features like QRS complex width, Form Factor and RR interval of an ECG signal are extracted and further the parameters of SVM are optimized by using Genetic Algorithm (GA). Experiments with different inputs are supervised to get optimal solution for PVC detection. On testing MIT physionet database, GSVM performs well in PVC detection with accuracy, sensitivity and specitivity of 99.5%, 98% and 100.