Paper Contents
Abstract
The accuracy of electrocardiogram (ECG) signals, which are essential for diagnosing cardiac disorders, is frequently compromised by a variety of noise sources, including muscle artifacts and power-line interference. This paper introduces a model-based method for removing noise from ECG signals using digital filtering techniques that are implemented in Simulink and MATLAB. The suggested technique uses a 50 Hz notch filter to remove power-line interference and a 40 Hz low-pass filter to reduce high-frequency noise. The output that results from applying these filters to noisy ECG data shows a marked improvement in clarity, making it possible to see heartbeat patterns and QRS complexes clearly. The usefulness of the suggested filtering technique in improving signal quality for precise medical diagnosis is confirmed by the comparison of noisy and filtered signals.
Copyright
Copyright © 2025 Mrunalini Bhandarkar, Shravni Gamne, Saniya Dumore. This is an open access article distributed under the Creative Commons Attribution License.
