Intelligent diagnosis method of cardiovascular anomalies using medical signal processing

Several studies have been performed on medical signal processing with the aim of enriching the table in diagnosis of heart disease. These signals include the ECG signal (electrocardiogram), ICG signal (impedance cardiogram), Doppler signal, phonocardiogram signal. However, the majority of the work in this area remains targeted on a specific signal type and are often reduced to limited or incomplete analysis methods. The objective of this work is to perform an intelligent method of non invasive and automatic diagnosis based on the processing of the ICG corresponding to the aorta impedance variation and the ECG signal during the heart cycle activity. Our method permits to perform automatic diagnosis of the cardiovascular anomalies via a graphical interface using Matlab. Automatic diagnosis method consists on preparing, first, a data base with a set of temporal spectral and cepstral parameters of different ICG and ECG according to different cardiac diseases. This data base is composed from n classes Yk corresponding to n diseases. The classification of anonymous individuals is based on the use of Fischer formula. The major interest of this method is its especially useful for the exploration of cardiovascular system anomalies for emergency cases, children, elderly and pregnant women who can't support surgical operations especially at the level of the heart.