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

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 9^th 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 9^th 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.