Ensemble empirical mode decomposition based ECG noise filtering method

Abstract

Electrocardiogram is often corrupted by various noises, such as high-frequency muscle contraction. In this study, ensemble empirical mode decomposition (EEMD) was used for ECG noise reduction. Gaussian noise was applied and the average (ensemble) intrinsic mode function (IMF) was used for ECG reconstruction. Three high frequency ECG noises; muscle contraction, 50 Hz power line interferences and Gaussian noise were examined. Mean square error (MSE) between filtered ECG and clean ECG was used as a reconstruction performance index. Results showed that the first two IMF levels were deleted owing to their noise components, while the other ensemble IMF constituted clean ECG components for ECG reconstruction. The MSE of EEMD is lower than EMD and IIR filter on these three noise types due to the reduction of mode-mixing effect between separate IMFs.