Abstract

ECG signals often are mixed with the myo-electrical interference, the power frequency interference and the baseline drift, and traditional filtering methods have certain shortcomings, which badly impact on the detection and the analysis of ECG (electrocardiogram) signals, so we use wavelet transform to filter out noise interferences of ECG signals for the above mentioned problem. Firstly, coif4 wavelet is adopted to scale decompose ECG signals containing noises, secondly, the soft and hard threshold value quantify high-frequency coefficients of every scale, finally, the wavelet reconstructs high-frequency coefficients of every scale which are quantified by the threshold value to get ECG signals being filtering. Experiments show that wavelet transform has well real-time and good filtering effect, and it has more obvious advantages more than traditional methods.

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