Coordinated Factor Analysis and Water Wave Optimization (WWO) Classifier for Classification of Arrhythmias from ECG Signal

The Electrocardiogram (ECG) is a bioelectric record of heart activity. ECG signal classification is crucial for heart disease diagnosis. It is difficult to make an appropriate ECG classification. In this study, MIT-BIH Arrhythmia ECG data base from physionet has been used to classify Cardiogram Signals. The very first, raw ECG signal is preprocessed by using noise cancellation (filtering) methods are Adaptive noise cancellation techniques, low pass linear noise cancellation techniques and high pass linear filter. After preprocessing reduces the dimensionality of data by using Coordinated Factor Analysis (CFA) and finally, dimensionally reduced signals are classified by using Water Wave Optimization (WWO) classifier. The Performance metrics like Performance Index, Accuracy, Sensitivity, and Specificity are evaluated using WWO to analyze the classification of arrhythmias from ECG signals.