Denoising of ECG Signals Using FIR & IIR Filter: a Performance Analysis

Abstract

Electrocardiogram (ECG) signal is a bio-electrical activity of the heart. It is a common routine and important cardiac diagnostic tool where in electrical signals are measured and recorded to know the functional status of heart, but ECG signal can be distorted with noise as, various artifacts corrupt the original ECG signal and reduces it quality. Therefore, there is a need to remove such artifacts from the original signal and improve its quality for better interpretation. Digital filters are used to remove noise error from the low frequency ECG signal and improve the accuracy the signal. Noise can be any interference due to motion artifacts or due to power equipment that are present where ECG had been taken. Thus, ECG signal processing has become a prevalent and effective tool for research and clinical practices. This paper presents the comparative analysis of FIR and IIR filters and their performances from the ECG signal for proper understanding and display of the ECG signal.

Pre-processing of ECG signal based on multistage filters

“…Thus, signal processing is essential for reducing noise on pertinent ECG signals and enhancing their effectiveness and quality [14]. In light of this, Mohammed Abbas Waheed [17]. The effectiveness of the employed filters has been evaluated in terms of removing high noise frequencies and low noise frequencies from the ECG signal.…”

Some Remarks about Entropy of Digital Filtered Signals

“…The process of digital filtering is extensively used in many applications in communications, signal processing, electrical and biomedical engineering, and control [ 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 ]; for example, coding and compression, signal augmentation, denoising, amplitude and frequency demodulation, analog-to-digital conversions, shape detection, and extraction [ 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 ]. For some applications, nonlinearity is tailored to a specific purpose [ 26 ].…”