COMPARISON OF DIFFERENT WAVELET FUNCTIONS FOR NOISE REMOVAL IN ECG SIGNAL

Abstract

Electrocardiogram is the graphical recording of the electrical activity of the heart and is recognized as the biological signal used for clinical diagnosis. The ECG signal is complex in nature, and even if small noise is mixed with actual signal the numerous characteristics of the signal undergoes variation. The signal voltage level is as low as 0.5 to 5mV and is susceptible to artifacts that are larger than it. The frequency components of a human ECG signal fall into the range of 0.05 to 10011z and as far as the noise is concerned; the muscle movements, power line interface and ambient electromagnetic interference generate it. Hence filtering remains an important issue, as data corrupted with noise must either be filtered or discarded. In this report the emerging roles of the wavelet transform in ECG preprocessing and noise removal have been discussed in a step for step approach. One of the most important causes of noise is baseline wander that effect ECG signal analysis has been removed by using a new method on wavelet transform is being proposed. So baseline wander removal is very important for the classification and analysis of ECG signal. The wavelet transform is one of the useful tools for removing these noises. Mother wavelet has become an effective tool to show the non stationary signals such as the repeated patterns of the recorded ECG signals. The selection of appropriate mother wavelet for the ECG signal is a challenging task. Various potential mother wavelet functions (Daubechies, Coiflets, Biorthogonal, Reverse Biorthogonal, Discrete Meyer and Symlets) have been discovered. Different parameters like the minimum mean square error (MSE), larger signal-to-noise (SNR) ratio and minimum percentage RMS difference (PRD) are considered for choosing a compatible mother wavelet function with the ECG signal. The results showed that the performance of Biorthogonal (bior3.9) for de-noising is the best among all mother wavelet functions