Least-Mean-Square algorithm based adaptive filters for removing power line interference from ECG signal

Abstract

The 50 Hz power line is one of the main sources of interference in ECG signal measurement, and it distorts the original ECG signal while recording. Recently, adaptive filtering has become one of the effective and popular methods for the processing and analysis of the ECG signal. In this study, we have used adaptive filters to remove the power line interference from the ECG signal. We have used different adaptive filter algorithms, such as, Least-Mean-Square (LMS), Block LMS (BLMS), Delay LMS (DLMS), Adjoint LMS, Filtered-X (XLMS), Normalized LMS (NLMS) and Fast Fourier Transform BLMS (FFT BLMS). We have used the Signal Processing Toolbox of the mentioned algorithms built in MATLAB <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">®</sup> . It reveals that among all the adaptive filters, the adaptive NLMS filter removes the 50 Hz power line interference more effectively.