A non invasive and automatic Bioimpedance method is used to explore the cardiovascular system. The objective of this work is to perform automatic diagnosis by processing the ICG signal which represents the aorta impedance variation during the heart cycle activity. ICG is detected by mean of two electrodes located at the level of the ascendant aorta. Automatic diagnosis method consists on preparing, first, a data base with a set of N cepstral parameters of 140 different normal cardiovasculars diseases. This data base corresponds to 14 classes Yk with 13 different cardiovascular diseases and 10 normal class. The classification of anonymous individuals is based on the determination of Fisher and Mahalanobis distance between anonymous disease and class Yk. Our method permits to calculate seven relevant cepstral parameters. The application of the discrimant analysis method has allows us to perform the diagnosis of 30 anonymous cases. The results found in this work indicate that 7 cepstral parameters are sufficient to perform the automatic diagnosis of the cardiovascular system abnormalities with 96.45% of percentage of correctly classified 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.
['Tareq Alhadidi', 'Ridha Ben Salah']
A new intelligent method for the automatic diagnosis of cardiovascular anomalies