Key result
The combination of the EMD method and the Choi-Williams time-frequency technique effectively filtered noise and extracted QRS complexes to detect anomalies in an abnormal ECG signal.
Combining Empirical Mode Decomposition with the Choi-Williams technique effectively filters noise and extracts key components like QRS complexes from abnormal ECG signals.
EMD-based ECG processing may aid noisy signal analysis; leaves open prospective clinical validation before practice change.
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.
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Dliou et al. (2012) studied Supraventricular arrhythmia (n=1). Combination of Empirical Mode Decomposition (EMD) and Choi-Williams time-frequency technique was evaluated on Extraction of signal components (QRS complexes) and anomaly detection. The combination of the EMD method and the Choi-Williams time-frequency technique effectively filtered noise and extracted QRS complexes to detect anomalies in an abnormal ECG signal.
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