A Software Tool for ECG Denoising with Adaptive Filtering

The electrocardiogram (ECG) is a biomedical signal used to check heart functions and diagnose some diseases. In order for these assessing to be made correctly, the relevant signals must be well cleared of noise. Many methods have been developed for this purpose. In this study we designed a new software tool by collecting many adaptive algorithms for ECG denoising. This tool was developed with a user-friendly graphical interface and comprises the loading of signals, their preprocessing, visualization, and single or comparative denoising. Some of the strengths and different aspects of the developed tool are that it contains many adaptive algorithms, can add different noise types with specified characteristics to the signals, can perform single or comparative denoising operations, can calculate and present many evaluation parameters, can recommend the most successful method in comparative analysis, and shows detailed spectrums of signals. Additionally, this tool provides detailed theoretical information about adaptive algorithms, noises and denoising processing. With its rich content, it is also useful in education of adaptive algorithms in denoising processes.