Denoising of Power line interference at Negative SNR Contaminated Electrocardiogram signal using Kalman Filter

Abstract

Identifying and determining various human illnesses requires a phase of visual inspection of biological signals by medical professionals. An effective and non-invasive marker for arrhythmia prevention and identification is the electrocardiogram (ECG). ECG signals are prone to noise contamination in real-world environments, which could result in incorrect interpretation. Thus, the denoising of the ECG has received much attention to providing precise diagnosis and monitoring. Therefore, this paper offers ECG denoising in highly contaminated environments using a Kalman filter (KF). The effectiveness of the proposed method has been evaluated by addingpowerline interference (PLI) at both 50 and 60 Hz at -30 to -10 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 &for 60 Hz: 21.85- 23.74 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 Hz: 10.75-12.78 dB).