Improved EASI ECG method as a future tool in diagnostics of patients suffering from noncommunicable diseases (NCDs)

Electrocardiography, technique, which is the essential tool in the diagnosis of heart disease, as well as other organs, is used by doctors for over 100 years. It is used to measure electrical activity of the heart as a function of time and it presents it in digital or analogue form. The measurement is usually recorded from the body surface of the patient, which makes the standard electrocardiogram completely devoid of pain. Whilst the standard 12 lead ECG is the basic clinical method of heart diagnosis it has its drawbacks. Measuring all 12 leads is often difficult and impractical, most of all it restricts patient movement. In 1988, Gordon Dower developed a system of quasi-orthogonal lead called EASI, which uses only 5 electrodes in order to register standard 12 lead ECG signals. The main goal of this work is to develop a model using machine learning algorithms which transforms electrocardiographic signals (ECG) performed by EASI into a standard 12-channel ECG. EASI was proven to have high correlation with standard 12 lead ECG, it is easier an d faster to use because of smaller number of electrodes. Most of all it increases mobility of patients.