Daubechies wavelet decomposition based baseline wander correction of trans-abdominal maternal ECG

Abstract

The paper presents an improved morphological approach for baseline wander correction in trans-abdominal electrocardiogram (ECG) signals, with emphasis on preserving all required clinical information of the original signal. The algorithm consists of morphological processing of sampled ECG signal using 9th order Daubechies wavelet transform. The morphological operators are applied to extract the baseline drift of the trans-abdominal ECG signal of a pregnant subject. The baseline signal is then subtracted from the input signal to leave a baseline normalized signal. The proposed algorithm has been successfully applied on the trans-abdominal ECG of a pregnant subject where the ECG signal has suffered considerable baseline drift due to excessive respiration as well as skeletal muscular contraction. For a quantitative validation of the estimation procedures, 10 ECG with artificial baseline drift were constructed and analyzed by correlation and mean square error calculations. Using the proposed 9th order Daubechies wavelet decomposition technique, the mean square error after baseline correction has been found to be less than 1%. Compared with all existing morphological methods, there is a substantial improvement in reducing distortion of the baseline waveform in any part of the signal.