To Compare Various Filters for Removal of Noise From ECG Wave

Abstract

The ECG (Electrocardiogram) signal is continuous in nature and abruptly changing. For taking intelligent health care decisions related with heart diseases such as paroxysmal of heart, arrhythmia diagnosing, ECG signal needs to be pre-process accurately for the further action on it such as extracting the features, wavelet decomposition, distribution of QRS complexes in ECG recordings and related information such as heart rate, classification of the signal by using various classifiers etc. Digital filters plays very significant role in the analysis of the low frequency components in ECG signal. Numbers of biomedical signals are of low frequency as the basic bandwidth used for the ECG monitoring is from 0.5 Hz to 60 Hz therefore removal of baseline wander and power line interference is a very important step at the pre-processing stage of ECG. Thus to obtain significant results, we have two approaches i.e. filtering approach and wavelet based approach accounting Signal to Noise Ratio, Mean Square Error as performance parameters. During the time we observed that S. Golay filter gives best results among all and we also find that Wavelet Transform method is also very effective for all types of noise which we will look upon later in the coming time. All the observations and results have been simulated on MATLAB.