Research of removing noise in ECG signal based on morphology and lifting wavelet

ECG is a typical weak noise-corrupted signal, with strong non-linear and non-stationary feature. It is difficult for traditional wavelet de-noise algorithm to remove the high- and low- frequency noise concurrently and the computation expense is large. The method that combines morphology and lifting wavelet threshold de-noise is able to remove the low frequency noise by a morphological filter and suppress the high frequency noise by the lifting wavelet de-noise. Based on the data from MIT-BIH arrhythmia database, the simulation results show that the proposed method is capable to remove the high- and low-frequency noise of the ECG signal concurrently and improve the ECG signal quality. ©, 2015, Beijing Institute of Technology. All right reserved.