Aiming at the problem that the noise such as baseline drift
power frequency and myoelectric interference in the ECG signal interferes with subsequent signal analysis and diagnosis
an ECG adaptive denoising method with ensemble empirical mode decomposition(EEMD)and improved threshold function is proposed. The noisy ECG signal is firstly decomposed into a set of intrinsic mode functions(IMFs)by EEMD. The IMFs are distributed from high frequency to low frequency. Then
-ero-crossing rate is used as a criterion to adaptively determine the noise category of each IMF. If the IMF contains high frequency noise
an improved threshold function in combination with the advantages and disadvantages of the soft and hard threshold functions is proposed to remove high frequency noise in the IMF component. If the IMF includes a low-frequency baseline drift
the median filter is chosen to suppress the baseline drift. Finally
all the processed IMFs are superimposed to reconstruct the de-noised ECG sig
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