Electrocardiogram beat classification via coupled boosting by filtering and preloaded mixture of experts

The role of electrocardiogram (ECG) as a noninvasive technique for detecting and diagnosing cardiac problems cannot be overemphasized. This paper introduces a modified version of boosted mixture of experts for the classification of three types of ECG beats. Our two-step preloading procedure, along noise injection, also regarded as smoothing regularization, proved to be a promising, effective, and safe means of classifying arrhythmias. The proposed model, according to the nature of implementation, is called coupled boosting by filtering and preloaded mixture of experts. The experimental results show our proposed method have better classification rate against other compared methods. Comparative evaluation is accomplished with ECG signals from MIT-BIH arrhythmia database.