NEW WAY TO PROCESS SIGNALS DIGITALLY

Abstract

Biomedical signal processing algorithms create a variety of opportunities to improve performance. This study proposed a new wavelet delta-function (WDF) method to effectively identify pathology from ECG signals. In this way, the delta function is determined for each value of the ECG signal. This is done through the WDF sum with a coefficient of 0, 1 and -1. The degree of difference between pathology and norm using data in the form of this vector allows you to make changes in diagnosis with greater accuracy than traditional methods. This is a new way to process EKG signals by converting graphical data into vectors. The new method has created a barcode-like image. Miocardial infarction (MI), one of the diseases of this cardiovascular system, has become more effective in real numbers of invisible peaks in the ECG. This makes it possible to identify the disease early and make a definitive diagnosis.
The model we propose is an effective way to analyze the ECG. The WDF model we have proposed can be used for early assessment of the disease when processing biomedical signals.