In this work, an algorithm was created to detect the characteristics of the electrocardiographic signal (ECG) of chronic Chagas patients from the State of Meta, Colombia and records of healthy people, using the Daubechies 5 wavelet (db 5), as an alternative way in the Fourier analysis for this type of signals.A database of 32 ECG records was created using a single channel with a 16-bits high resolution polygraph.This algorithm allowed the identification of the most important characteristics of each ECG record of patients with the disease, measuring the intervals and amplitudes of the waves and heart rate with an accuracy greater than 91%, becoming a tool for a better diagnosis of the symptoms of chronic Chagas disease.