Efficient Application of Kalman Filter for Enhancement of ECG Signal Visibility by Denoising Power Line Interference

In a post-pandemic era, health and wellness become a more prominent domain. Numerous researches are going on globally. Hence, medical professionals engaged with identifying many human illnesses like heart, brain, and lung diseases need a visual inspection of medical images and biological signals. An important domain for visually inspecting heart diseases is the electrocardiogram (ECG). An effective and non-invasive marker for arrhythmia prevention and identification is the ECG. ECG signals are prone to noise contamination in real-world environments, which could result in incorrect inter-pretation. Thus, the denoising of the ECG has received much attention to providing precise diagnosis and monitoring. There-fore, this paper offers ECG denoising in highly contaminated environments using a Kalman filter (KF). The effectiveness of the proposed method has been evaluated by adding powerline interference (PLI) at both 50 and 60 Hz at -30 to $\mathbf{-10} \mathrm{dB}$ input signal-to-noise ratio (SNR) to the Electrocardiograph record from the MIT-BIH arrhythmia databases. The obtained output SNR (for 50 Hz: 20.82 22.13 dB and for $60 \mathrm{~Hz}: 21.85-23.74 \mathrm{~dB}$) divulges the superiority of the KF methodology while assessing it with the notch filter (for 50 Hz: 12.04-16.36 dB and for $60 \mathrm{~Hz}: 10.75-12.78 \mathrm{~dB}$).