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ECG signal processing using multiresolution analysis

In this paper, multiresolution analysis using wavelets is discussed and evaluated in ECG signal processing. The approach we developed for processing the ECG signals uses two steps. In the first step, we implement an algorithm based on multiresolution analysis using discrete wavelet transform for denoising the ECG signals. The results we obtained on MIT-BIH ECG signals show good performance in denoising ECG signals. In the second step, multiresolution analysis is applied for QRS complex detection. It is shown that with such analysis, the QRS complex can be distinguished from high P or T waves, baseline drift and artefacts. The results we obtained on ECG signals from the MIT-BIH database show a detection rate of QRS complexes above 99.8% (sensitivity = 99.88% and predictivity = 99.89%), and a total detection failure of 0.24%.