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Noise Removing from ECG Signal Using FIR Filter with Windowing Techniques

Electrocardiogram (ECG) is a biological non-stationary signal, which contains valuable information about the rhythms of the heart. It detects cardiac abnormalities by measuring the electrical activity in the heart. 50 Hz power line interference (PLI) often distorts the original ECG signal while recording, and physicians are quite unable to diagnose a cardiac patient with this kind of noisy signal. So, it is reasonably required to reconstruct the signal by removing the PLI. This study presents an ECG signal de-noising process based on the finite impulse response (FIR) filtering approach with different windowing techniques, such as rectangular, Hanning, Hamming, Kaiser, Bartlett, triangle, Chebyshev, Taylor, modified Bartlett-Hann, and Blackman windows. Both qualitative and quantitative analyses are performed. The results are verified by observing single side-band frequency spectrum, power spectral density, magnitude squared coherence and spectrogram analyses. Different performance parameters, such as mean square error, root mean square error, percentage root mean square difference, signal to noise ratio, peak signal to noise ratio are also calculated. We also associated our study with the other researchers. The results reveal that various windowing techniques with FIR low-pass filters perform significantly well.