Performance Evaluation of Wavelet De-Noising Schemes for Suppression of Power Line Noise in Electrocardiogram Signals

Abstract

Power line noise introduces distortions to recorded electrocardiogram (ECG) signals. These distortions compromise the integrity and negatively affect the interpretation of the ECG signals. Despite the fact that the amplifiers used in biomedical signal processing have high common mode rejection ratio (CMRR), ECG recordings are still often corrupted with residual Power Line Interference (PLI) noise. Further improvement in the hardware solutions do not have significant achievements in PLI noise suppression but rather introduce other adverse effects. Software approach is necessary to refine ECG data. Evaluation of PLI noise suppression in ECG signal in the wavelet domain is presented. The performance of the Hard Threshold Shrinkage Function (HTSF), the Soft Threshold Shrinkage Function (STSF), the Hyperbola Threshold Shrinkage Function (HYTSF), the Garrote Threshold Shrinkage Function (GTSF), and the Modified Garrote Threshold Shrinkage Function (MGTSF) for the suppression of PLI noise are evaluated and compared with the aid of an algorithm. The optimum tuning constant for the Modified Garrote Threshold Shrinkage Function (MGTSF) is found to be 1.18 for PLI noise. GTSF is found to have best performance closely followed by MGTSF in term of filtering Gain. HTSF recorded the lowest Gain. Filtering against PLI noise in the wavelet domain preserves the key features of the signal such as the QRS complex.