Topographic analysis of morphologic features of ECG beats

In this work, the arrhythmias in the electrocardiograph (ECG) signals are analyzed by using self organizing maps (SOM). Morphologic features obtained from consecutive sample values of each R peak are used for training the SOM networks. The maps are examined using U-matrix representation method. Consequently, the high dimensional data are examined in two dimensions. When the shapes of the distributions obtained by U-matrix representation are considered, it is realized that a simple linear classifier is not able to classify these patterns correctly.