Removal of Artifacts from ECG Signal Using RLS Based Adaptive Filter: A Review

The electrocardiogram (ECG) is used for diagnosis of heart diseases. In a few circumstances the recorded ECG signals are corrupted by various noise signals caused by power line interference, base line wander, electrode movement, muscular movement (EMG) etc. These noise signals are known as artifacts. These artifacts mislead the diagnosis of heart which is not desired. To avoid this problem caused by artifacts, removal of these artifacts has become essential. There are various techniques which have been used for artifacts rejection from ECG. Conventional filters remove the artifacts up to some extent but these filters are static filters. These filters cannot update their coefficients with the change in environment where as adaptive filters update their coefficients according to the requirement. There are various adaptive algorithms such as Least Mean Square (LMS), Recursive Least Square (RLS), Normalized Least Mean Square (NLMS) etc. This paper deals with RLS algorithm for removal of artifacts from ECG signal. The filter algorithm is designed using MATLAB and tested on ECG signal corrupted with various artifacts.