Adaptive Filter Design for ECG Noise Reduction using LMS Algorithm

Abstract— The adaptive filters algorithms for removing noise from the Electrocardiogram to receive noise less pure embryo signals. Filtering ECG signals requires a filter which can automatically adapt according to changing input and noise. Adaptive filtering has been used to reduce the noise from the desired ECG signals by using LMS algorithm. Other algorithms like NLMS and RLS can also be used but LMS gives least MMSE amongst them so it can be used where accuracy is required. The measures of performance contains the optimization between the rate of convergence and MMSE by the help of MATLAB. The experimental results have shown that for small values of step size the rate of convergence increases. An Adaptive filter finds its application where the stable characteristics are not known or cannot be fulfilled by the time invariant filters. Adaptive filter direct modeling or system identification and adaptive inverse modeling or channel equalization have wide applications in telecommunication, control system, instrumentation, power system engineering and geophysics. < final year projects >