Dynamic ECG features for atrial fibrillation recognition

This study / paper highlights on several aspects as follows: • The characterization of atrial fibrillation using second order dynamic system.• The optimum windowing length of ECG signal processing during normal sinus rhythm (NSR) and during atrial fibrillation (AF) with normal sinus rhythm (N) according to pattern recognition machine learning using an art ificial neural network (ANN) and a support vector machine (SVM) with k-fold cross validation (k-CV) to develop an ECG recognition system.• The study proposed a method based on dynamic system, which achieved high sensitivity and specificity and able to describe the oscillatory behavior of heart acc ording to the normal sinus rhythm of healthy people (NSR), normal (N) and abnormal sinus rhythms (AF) of atrial fibrillation patients ECG signals.

Source: Computer Methods and Programs in Biomedicine - August 30, 2016 Category: Bioinformatics Authors: Nurul Ashikin Abdul-Kadir, Norlaili Mat Safri, Mohd Afzan Othman Source Type: research