Estimation of normal and ischemia tissues, with different doses of vasopressin (AVP), through packet wavelet analysis of electrocardiogram and atrial blood pressure signals

Coronary congestion is a heart disease, putting many lives at risk each year. The task of coronary arteries is to distribute blood to heart tissues, and any blockage in them can cause the tissue to feed the oxygen and nutrients less than their needs (ischemia disease), This imbalance will continue until the first cell is destroyed (myocardial infarction).In this paper, with simulated myocardial infarction in laboratory rats, we were trying to determine the extent of tissue damage through electrocardiogram (ECG) and atrial blood pressure (ABP) synchronic signals. Signals of ۵۰ wistar rats, with a weight range of ۲۰۰-۳۰۰ g, were recorded ۳۰ minutes in normal case and ۳۰ minutes in ischemia and myocardial infarction case (the artificial complete blockage was in the left anterior descending coronary artery (LAD)). For a different injury in the rats heart, we injected the AVP with different doses for ۴۰ rats. After images of the heart sections and data were extracted, the ۵۰-dimensional feature vector was generated using the packet wavelettransform (PWT) on the ECG and ABP signals and obtaining the entropy of wavelet coefficients. The extent of tissue damage on the images of the heart tissue was extracted using image processing method. Finally, four artificial neural networks (ANN) (with different structures) with averaging criteria estimated the amount of the damaged tissue.Our intelligent machine estimated ischemia and normal tissues with average error ۲.۹۱% for all the AVP doses and control cases.