ECG Filtering Algorithm Using Mathematical Morphology

This article discusses an algorithm for filtering electrocardiogram (ECG) signals using mathematical morphology. The algorithm is completely original and does not utilize MATLAB's built-in functions. ECG is a commonly used examination method for diagnosing heart diseases. By applying filtering techniques to ECG data, we can remove various interference signals, enabling more accurate analysis of the cardiac waveforms. Mathematical morphology serves as an effective signal processing method applicable across multiple domains. In this algorithm, we employ mathematical morphology techniques to filter ECG data and enhance signal accuracy. The implementation involves fundamental morphological operations including dilation and erosion with carefully selected structuring elements to preserve QRS complex characteristics while removing baseline wander and high-frequency noise. The complete source code will be detailed in subsequent sections, showcasing the custom implementation of morphological filters that outperform standard filtering approaches in preserving important clinical features of ECG signals.