Noised abnormal ECG signal analysis by combining EMD and Choi-Williams techniques

Due to the wide variety of biomedical signals, such as the electrocardiogram (ECG) signal, and problems encountered in medicine and biology a good diagnostic is very important to detect the real pathology contained in the signal. In one hand the presence of the noise and in the other hand the non-stationary multicomponent nature of the electrocardiogram (ECG) signal present the major problems that can influence in the analysis of such biomedical signal. In this paper, the Empirical Mode Decomposition (EMD) and the Choi-Williams time frequency technique were applied to a noised abnormal ECG signal. In the first time, the EMD method is used as a pretreatment to filter the noise from the noised abnormal ECG signal. In the second time, the Choi-Williams time-frequency technique is applied to extract different components of the resulting signal, especially the QRS complexes, and detecting the anomaly present in the latter. The abnormal studied signal was taken from a patient with supraventricular arrhythmia. The analysis results show that the combination of the EMD method and the Choi-Williams time-frequency technique can be an effective approach to analyze the noised abnormal ECG signals.