Block Entropy analysis of long recorded Electrocardiograms as a good way for discrimination between Normal subjects and Coronary patients

Heart Rate Variability timeseries of long recordings of Electrocardiograms are filtered in order to generate a coarse grained linguistic dynamics. Then the Block Entropy analysis is applied in order to analyze the coarse grained statistics. The set of the timeseries is separated in two categories : Normal subjects, and Coronary patients. The entropy analysis provides a quick and efficient tool for discrimination of the timeseries according to these categories. Healthy subjects provided more complex statistics compared to patient ones. In particular the healthy data files provided higher values of block Entropies compared to patient ones. Furthermore all this analysis may provide a useful statistical way to the understanding of the human cardiac system.