Denoising Ventricular tachyarrhythmia Signal

Electrocardiogram signals (ECG) are among the most important sources of diagnostic information in healthcare. During ECG measurement, there may be various noises such as muscle contraction (electromyography), baselines wander, and power-line interferences, which interfered with the ECG information identification that causing a misinterpretation of the ECG signal. In this paper, the denoising techniques of the Empirical Mode Decomposition (EMD), the Ensemble Empirical Mode Decomposition (EEMD) and the Discrete Wavelet Transform (DWT) were used. These techniques are applied to a noisy electrocardiogram abnormal signal obtained by adding white noise and natural noise. A comparative performance study of these three techniques was used. The abnormal signal used is obtained from the patient with a malignant ventricular arrhythmia. From the obtained results, the EEMD technique is a powerful tool for elimination and restoration the original signal than the other techniques used in this paper.