For the identification and diagnosis of numerous heart-related disorders, ECG signals are frequently employed. A recent application that is expanding quickly at the moment is feature extraction using ECG. A multitude of factors, including baseline wander interference, motion artefact, equipment noise, electrode contact noise, EMG noise, and others can contaminate the ECG signal as it is being acquired. Kaiser, Rectangle, Hamming, Hanning, and Welch windows were used. MSE, SNR, Positive Peak, and THD performance measures for power line interference, muscle noise, and EMG noise were used to analyse and compare the output. This study provides an ideal ECG noise elimination windowing system that determines which window should be used for a specific noise type.

ECG: Electro cardio graphy; MSE: Mean Square Error; SNR: Signal to Noise Ratio; THD: Total Harmonic Distortion.