Transactions on Machine Intelligence 2821-1693 6 1 2023 03 01 An Investigation on The performance of Infinite Impulse Response Filters in Denoising Electrocardiogram Signals 10 15 181343 10.47176/TMI.2023.10 EN N. Derogar Jahromi Faculty of Engineering, Jahrom University, Jahrom, Iran H. Dehdashti Jahromi Faculty of Engineering, Jahrom University, Jahrom, Iran Journal Article 2022 12 07 Electrocardiogram (ECG) signals play a vital role in the clinical assessment of cardiac function, enabling the diagnosis of various heart disorders and the monitoring of treatment outcomes. However, these signals are frequently contaminated by diverse sources of noise, including electromagnetic interference from urban environments (such as 50 Hz powerline noise), muscle activity (electromyographic signals), and even neurological signals. These unwanted signal components, collectively referred to as "noise," can significantly degrade the quality of the ECG waveform, complicating both visual inspection and automated analysis. To ensure the accurate interpretation of ECG recordings, it is essential to employ effective signal processing techniques that can suppress noise while preserving the integrity of diagnostically relevant features. In this study, we investigate and compare the performance of three Infinite Impulse Response (IIR) digital filters: Butterworth, Chebyshev Type I, and Chebyshev Type II. The primary objective is to attenuate the dominant 50 Hz interference commonly observed in urban clinical and research environments. Comprehensive simulations and tests on real ECG signals demonstrate that the Chebyshev Type I filter offers a particularly effective balance between sharp frequency selectivity and minimal signal distortion. Its performance in attenuating noise within both the passband and stopband makes it a favorable choice for preprocessing ECG data, thereby enhancing diagnostic accuracy in biomedical signal analysis applications. https://www.tmachineintelligence.ir/article_181343_59d198b0ac4b61dbf9da0e0a0e3ffb10.pdf