Abstract：The ensemble empirical mode decomposition(EEMD)combined with the interval threshold has achieved good results in ECG signal denoising,but there are some cases where the signal is not continuous after denoising.Aiming at this problem,a method combining the complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)with the improved interval threshold is proposed.Firstly,the ECG signal is decomposed with CEEMDAN to obtain the intrinsic mode functions.Based on the obtained intrinsic mode functions,the appropriate selection of the interval threshold reflecting the time domain characteristics of the signal is selected,and the eigenvalues of the high frequency components of the signal are selected.The intrinsic mode functions are processed to achieve high-frequency noise reduction;the baseline drift is removed based on the obtained zero-frequency characteristics of the intrinsic mode functions′zero-crossing rate.The experimental results show that by analyzing the real ECG signals,the proposed method reduces the discontinuity compared with the ensemble empirical mode decomposition combined with the interval threshold algorithm,so that the signal-to-noise ratio of the signal after denoising is higher and root mean square error is smaller.
徐利,徐久强,冯家乐. 结合CEEMDAN与改进区间阈值的ECG降噪研究[J]. 小型微型计算机系统, 2020, 41(8): 1576-1579.
XU Li,XU Jiu-qiang,FENG Jia-le. Research on ECG Denoising Combined with CEEMDAN and Improved Interval Threshold. Journal of Chinese Computer Systems, 2020, 41(8): 1576-1579.
2020, Vol. 41 
