Statistical filtering strategy for ECG noise reduction

Abstract

A straightforward and effective approach for eliminating artifacts and random noises from electrocardiogram signals is introduced. This method leverages fundamental digital signal processing techniques, including: moving average filtering, median filtering, baseline wandering rectification, and peak detection. Through extensive simulations, we demonstrate that the introduced technique is significantly better than the conventional cited filters, positioning it as a strong competitor to the standard waveletbased approach.